# MongoDB Atlas Source Connector for Confluent Cloud
The fully managed MongoDB Atlas Source connector for Confluent Cloud moves data from a
MongoDB replica set into an Apache Kafka® cluster. The connector configures and
consumes change stream event documents and publishes them to a Kafka topic.
#### NOTE
* [Sign up for a Confluent Cloud trial](https://www.confluent.io/get-started/) and get $400 of free credit.
* If you require private networking for fully managed connectors, make sure to set up the proper
networking beforehand. For more information, see [Manage Networking for Confluent Cloud Connectors](networking/internet-resource.md#clusters-connect-cloud).
## Features
The MongoDB Atlas Source connector supports both MongoDB Atlas and self-managed MongoDB databases.
The connector offers the following features:
* **At least once delivery**: The connector guarantees that records are delivered at least once to the Kafka topic.
* **Topics created automatically**: The connector automatically creates Kafka topics using the naming convention: `..`. The topics are created with the properties: `topic.creation.default.partitions=1` and `topic.creation.default.replication.factor=3`. You add the prefix when setting up the connection in the Quick Start steps. For more information, see [Maximum message size](#cc-mongodb-source-debezium-topic-sizing). Note that if you want to create topics with specific settings, create the topics before running this connector.
* **Database authentication:** The connector supports both username/password-based and X.509 certificate-based
authentication. For more information on MONGODB-X.509-based authentication setup,
see [connector authentication](#cc-mongo-db-source-setup-connection).
* **Output data formats:** The connector supports Avro, Byte, JSON (schemaless), JSON Schema, Protobuf or String output data. [Schema Registry](../get-started/schema-registry.md#cloud-sr-config) must be enabled to use a Schema Registry-based format (for example, Avro, JSON_SR (JSON Schema), or Protobuf).
* **Large size records:** The connector supports MongoDb documents up to 20 MB in size on Dedicated Kafka clusters and 8 MB on other clusters.
* **Select configuration properties:**
- `poll.await.time.ms`: The amount of time to wait before checking for new results in the change stream.
- `poll.max.batch.size`: The maximum number of change stream documents to include in a single batch when polling for new data. This setting can be used to limit the amount of data buffered internally in the connector.
* **Offset management capabilities**: The connector supports offset management. For more information, see [Manage custom offsets](#cc-mongodb-source-custom-offsets).
* **Secret manager integration**: The connector supports secret manager integration. For `SCRAM-SHA-256` (username and password) authentication, the connector can retrieve the following configurations from an integrated secret manager at runtime as needed.
| **Secret manager managed configuration** | **Type** |
|--------------------------------------------|------------|
| `connection.host` | `STRING` |
| `connection.user` | `STRING` |
| `connection.password` | `PASSWORD` |
For more information, see [Create a secret manager integration in Confluent Cloud](secret-manager-integration/overview.md#cloud-secret-manager-quickstart).
For more information and examples to use with the Confluent Cloud API for Connect,
see the [Confluent Cloud API for Connect Usage Examples](connect-api-section.md#ccloud-connect-api) section.
## Limitations
Be sure to review the following information.
* For connector limitations, see [MongoDB Atlas Source Connector](limits.md#cc-mongo-db-source-limits) limitations.
* If you plan to use one or more Single Message Transformations (SMTs), see [SMT Limitations](single-message-transforms.md#cc-single-message-transforms-limitations).
## Maximum message size
This connector creates topics automatically. When it creates topics, the internal connector configuration property `max.message.bytes` is set to the following:
* Basic cluster: `8 MB`
* Standard cluster: `8 MB`
* Enterprise cluster: `8 MB`
* Dedicated cluster: `20 MB`
For more information about Confluent Cloud clusters, see [Kafka Cluster Types in Confluent Cloud](../clusters/cluster-types.md#cloud-cluster-types).
## Manage custom offsets
You can manage the offsets for this connector. Offsets provide information on the
point in the system from which the connector is accessing data. For more
information, see [Manage Offsets for Fully Managed Connectors in Confluent Cloud](offsets.md#connect-custom-offsets).
**To manage offsets**:
- Manage offsets using Confluent Cloud APIs. For more information, see [Connect offsets API reference](https://docs.confluent.io/cloud/current/ccloud/offsets-connect-v-1/).
### Get the current offset
To get the current offset, make a `GET` request that specifies the environment, Kafka cluster, and connector name.
```bash
GET /connect/v1/environments/{environment_id}/clusters/{kafka_cluster_id}/connectors/{connector_name}/offsets
Host: https://api.confluent.cloud
```
**Response:**
Successful calls return HTTP `200` with a JSON payload that describes the offset.
```bash
{
"id": "lcc-example123",
"name": "{connector_name}",
"offsets": [
{
"partition": {
"ns": "mongodb+srv://cluster0.2a5tnof.mongodb.net/"
},
"offset": {
"_id": "{\"_data\": \"82661F7DDE000000012B042C0100296E5A1004737030_TRUNCATED\"}"
}
}
],
"metadata": {
"observed_at": "2024-03-28T17:57:48.139635200Z"
}
}
```
Responses include the following information:
- The position of latest offset.
- The observed time of the offset in the metadata portion of the payload. The `observed_at` time
indicates a snapshot in time for when the API retrieved the offset. A running connector is always updating
its offsets. Use `observed_at` to get a sense for the gap between real time and the time at which the request
was made. By default, offsets are observed every minute. Calling `GET` repeatedly will fetch more recently
observed offsets.
- Information about the connector.
### Update the offset
To update the offset, make a `POST` request that specifies the environment, Kafka cluster, and connector
name. Include a JSON payload that specifies new offset and a patch type.
```bash
POST /connect/v1/environments/{environment_id}/clusters/{kafka_cluster_id}/connectors/{connector_name}/offsets/request
Host: https://api.confluent.cloud
{
"type": "PATCH",
"offsets": [
{
"partition": {
"ns": "mongodb+srv://cluster0.2a5tnof.mongodb.net/"
},
"offset": {
"_id": "{\"_data\": \"82661F7DDE000000012B042C0100296E5A100473703049_TRUNCATED\"}"
}
}
]
}
```
Considerations:
- You can only make one offset change at a time for a given connector.
- This is an asynchronous request. To check the status of this request, you must use the check offset status API. For more information,
see **Get the status of an offset request**.
- For source connectors, the connector attempts to read from the position defined by the requested offsets.
**Response:**
Successful calls return HTTP `202 Accepted` with a JSON payload that describes the offset.
```bash
{
"id": "lcc-example123",
"name": "{connector_name}",
"offsets": [
{
"partition": {
"ns": "mongodb+srv://cluster0.2a5tnof.mongodb.net/"
},
"offset": {
"_id": "{\"_data\": \"82661F7DDE000000012B042C0100296E5A1004737030_TRUNCATED\"}"
}
}
],
"requested_at": "2024-03-28T17:58:45.606796307Z",
"type": "PATCH"
}
```
Responses include the following information:
- The requested position of the offsets in the source.
- The time of the request to update the offset.
- Information about the connector.
### Delete the offset
To delete the offset, make a `POST` request that specifies the environment, Kafka cluster, and connector
name. Include a JSON payload that specifies the delete type.
```bash
POST /connect/v1/environments/{environment_id}/clusters/{kafka_cluster_id}/connectors/{connector_name}/offsets/request
Host: https://api.confluent.cloud
{
"type": "DELETE"
}
```
Considerations:
- Delete requests delete the offset for the provided partition and reset to the base state. A
delete request is as if you created a fresh new connector.
- This is an asynchronous request. To check the status of this request, you must use the check offset status API. For more information,
see **Get the status of an offset request**.
- Do not issue delete and patch requests at the same time.
- For source connectors, the connector attempts to read from the position defined in the base state.
**Response**:
Successful calls return HTTP `202 Accepted` with a JSON payload that describes the result.
```bash
{
"id": "lcc-example123",
"name": "{connector_name}",
"offsets": [],
"requested_at": "2024-03-28T17:59:45.606796307Z",
"type": "DELETE"
}
```
Responses include the following information:
- Empty offsets.
- The time of the request to delete the offset.
- Information about the Kafka cluster and connector.
- The type of request.
### Get the status of an offset request
To get the status of a previous offset request, make a `GET` request that specifies the environment, Kafka cluster, and connector
name.
```bash
GET /connect/v1/environments/{environment_id}/clusters/{kafka_cluster_id}/connectors/{connector_name}/offsets/request/status
Host: https://api.confluent.cloud
```
Considerations:
- The status endpoint always shows the status of the most recent PATCH/DELETE operation.
**Response**:
Successful calls return HTTP `200` with a JSON payload that describes the result. The following is an example
of an applied patch.
```bash
{
"request": {
"id": "lcc-example123",
"name": "{connector_name}",
"offsets": [
{
"partition": {
"ns": "mongodb+srv://cluster0.2a5tnof.mongodb.net/"
},
"offset": {
"_id": "{\"_data\": \"82661F7DDE000000012B042C0100296E5A100473703_TRUNCATED\"}"
}
}
],
"requested_at": "2024-03-28T17:58:45.606796307Z",
"type": "PATCH"
},
"status": {
"phase": "APPLIED",
"message": "The Connect framework-managed offsets for this connector have been altered successfully. However, if this connector manages offsets externally, they will need to be manually altered in the system that the connector uses."
},
"previous_offsets": [
{
"partition": {
"ns": "mongodb+srv://cluster0.2a5tnof.mongodb.net/"
},
"offset": {
"_id": "{\"_data\": \"82661FF4CF000000042B042C0100296E5A100473703049_TRUNCATED\"}"
}
}
],
"applied_at": "2024-03-28T17:58:48.079141883Z"
}
```
Responses include the following information:
- The original request, including the time it was made.
- The status of the request: applied, pending, or failed.
- The time you issued the status request.
- The previous offsets. These are the offsets that the connector last updated
prior to updating the offsets. Use these to try to restore the state of your connector
if a patch update causes your connector to fail or to return a connector to its
previous state after rolling back.
### JSON payload
The table below offers a description of the unique fields in the JSON payload for managing offsets of the MongoDB Atlas Source connector.
| Field | Definition | Required/Optional |
|---------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------|
| `ns` | `ns` is the connection string, including the connection host. If the configuration file for
the connector includes a value in `offset.partition.name`, the value in `offset.partition.name` is used for `ns`. | Required |
| `_id` | `_id` is the `_data` field from the source record in MongoDB. | Required |
## Quick Start
Use this quick start to get up and running with the Confluent Cloud MongoDB Atlas
Source connector. The quick start provides the basics of selecting the connector
and configuring it to consume data from MongoDB and persist the data to Kafka.
Prerequisites
: - Authorized access to a [Confluent Cloud](https://www.confluent.io/confluent-cloud/) cluster on Amazon Web Services (AWS), Microsoft Azure (Azure), or Google Cloud.
- The Confluent CLI installed and configured for the cluster. See [Install the Confluent CLI](https://docs.confluent.io/confluent-cli/current/install.html).
- [Schema Registry](../get-started/schema-registry.md#cloud-sr-config) must be enabled to use a Schema Registry-based format (for example, Avro, JSON_SR (JSON Schema), or Protobuf).
- Access to a MongoDB database. Note that the connection user must have **privileged action “find”** to query the MongoDB database. For more information, see [Query and Write Actions](https://docs.mongodb.com/manual/reference/privilege-actions/#query-and-write-actions).
- The MongoDB hostname address must provide a service record (SRV) when connecting to MONGODB_ATLAS. For MONGODB_SELF_MANAGED, a standard connection string is required.
- The connector automatically creates Kafka topics using the naming convention: `..`. The topics are created with the properties: `topic.creation.default.partitions=1` and `topic.creation.default.replication.factor=3`. If you want to create topics with specific settings, create the topics before running this connector.
#### IMPORTANT
If you are configuring granular access using a [service account](service-account.md#s3-cloud-service-account), and you leave the optional **Topic prefix**
(`prefix`) configuration property empty, the connector uses the
**Database name** (`database-name`) entered as the prefix. You must grant ACL
`CREATE` and `WRITE` access to the database name prefix (see [ACL
access](service-account.md#cloud-service-account-jdbc-mongo-acls)). If both the
`prefix` and `database-name` configuration properties are not used, you
must do one of the following:
- If you know the databases to capture, create individual ACLs for each
topic. The topic name will have the database name as the prefix.
- Create ACLs for all Kafka topics, using the (\*) wildcard in the ACL entries
as shown below:
```bash
confluent kafka acl create --allow --service-account
"" --operation create --topic "*"
.. code-block:: bash
confluent kafka acl create --allow --service-account
"" --operation write --topic "*"
```
- Create create [RBAC role bindings](managed-connector-rbac.md#managed-connector-rbac).
- If you have a VPC-peered cluster in Confluent Cloud, consider configuring a [PrivateLink Connection](https://docs.atlas.mongodb.com/security-private-endpoint/#configure-an-service-private-endpoint) between MongoDB Atlas and the VPC. For additional networking considerations, see [Networking and DNS](overview.md#connect-internet-access-resources). To use a set of public egress IP addresses, see [Public Egress IP Addresses for Confluent Cloud Connectors](static-egress-ip.md#cc-static-egress-ips).
- Kafka cluster credentials. The following lists the different ways you can provide credentials.
- Enter an existing [service account](service-account.md#s3-cloud-service-account) resource ID.
- Create a Confluent Cloud [service account](service-account.md#s3-cloud-service-account) for the connector. Make sure to review the ACL entries required in the [service account documentation](service-account.md#s3-cloud-service-account). Some connectors have specific ACL requirements.
- Create a Confluent Cloud API key and secret. To create a key and secret, you can use [confluent api-key create](https://docs.confluent.io/confluent-cli/current/command-reference/api-key/confluent_api-key_create.html) *or* you can autogenerate the API key and secret directly in the Cloud Console when setting up the connector.
### Using the Confluent Cloud Console
#### Step 1: Launch your Confluent Cloud cluster
To create and launch a Kafka cluster in Confluent Cloud, see [Create a kafka cluster in Confluent Cloud](../get-started/index.md#cloud-create-kafka-cluster).
#### Step 2: Add a connector
In the left navigation menu, click **Connectors**. If you already have connectors in your cluster, click **+ Add
connector**.
#### Step 3: Select your connector
Click the **MongoDB Atlas Source** connector card.
#### Step 4: Enter the connector details
#### NOTE
* Make sure you have all your [prerequisites](#cc-mongo-db-source-prereqs) completed.
* An asterisk ( \* ) designates a required entry.
* You can specify connection string options in the connection host. For example: `cluster4-r5q3r7.gcp.mongodb.net/?readPreference=secondary&readConcernLevel=local`. For more information about connection string options, see [MongoDB Connection String Options](https://www.mongodb.com/docs/manual/reference/connection-string-options/#std-label-connections-connection-options).
#### NOTE
* The connector does not support following connection string options in `connection.host`
config: `tlsCertificateKeyFile`, `tlsCertificateKeyFilePassword`, `tlsCAFile`,
`tlsAllowInvalidCertificates`, `tlsInsecure`, `tlsAllowInvalidHostnames`,
`authMechanism`, `authMechanismProperties`, `gssapiServiceName`.
* Other options like `readPreference`, `readConcernLevel`, or `w` defined in
[MongoDB Connection String Options](https://www.mongodb.com/docs/manual/reference/connection-string-options/#std-label-connections-connection-options)
can be configured in `connection.host` configuration. For example,
`cluster4-r5q3r7.gcp.mongodb.net/?readPreference=secondary&readConcernLevel=local&appName=test&w=majority`.
* The connector supports connecting to self-managed MongoDB database.
: Use `mongodb.instance.type` as MONGODB_SELF_MANAGED and specify the `connection.host` accordingly
to connect to self-managed instance. For example, `54.190.171.123:27017/?authSource=admin`.
At the **MongoDB Atlas Source Connector** screen, complete the following:
### Define a topic prefix
In the **Topic prefix** field, define a topic prefix your connector will
use to publish to Kafka topics. The connector will Kafka topics using the
following naming convention: `..`. If you want to
create topics with specific settings, create the topics before running
this connector.
#### IMPORTANT
If you are configuring granular access using a [service account](service-account.md#s3-cloud-service-account), and you leave the optional **Topic prefix**
(`prefix`) configuration property empty, the connector uses the
**Database name** (`database-name`) entered as the prefix. You must grant ACL
`CREATE` and `WRITE` access to the database name prefix (see [ACL
access](service-account.md#cloud-service-account-jdbc-mongo-acls)). If both the
`prefix` and `database-name` configuration properties are not used, you
must do one of the following:
- If you know the databases to capture, create individual ACLs for each
topic. The topic name will have the database name as the prefix.
- Create ACLs for all Kafka topics, using the (\*) wildcard in the ACL entries
as shown below:
```bash
confluent kafka acl create --allow --service-account
"" --operation create --topic "*"
.. code-block:: bash
confluent kafka acl create --allow --service-account
"" --operation write --topic "*"
```
- Create create [RBAC role bindings](managed-connector-rbac.md#managed-connector-rbac).
### Kafka access
1. Select the way you want to provide **Kafka Cluster credentials**. You can
choose one of the following options:
- **My account**: This setting allows your connector to globally access everything
that you have access to. With a user account, the connector uses an API key and
secret to access the Kafka cluster. This option is not recommended for production.
- **Service account**: This setting limits the access for your connector by using a
[service account](service-account.md#s3-cloud-service-account). This option is recommended for
production.
- **Use an existing API key**: This setting allows you to specify an API key and a
secret pair. You can use an existing pair or create a new one. This method is not
recommended for production environments.
#### NOTE
Freight clusters support only service accounts for Kafka authentication.
2. Click **Continue**.
### Authentication
1. Configure the authentication properties:
**MongoDB instance type**
- **MongoDB instance type**: Specify the MongoDB deployment type.
Use **MONGODB_ATLAS** for cloud hosted Atlas clusters or **MONGODB_SELF_MANAGED** for self hosted MongoDB instances.
**MongoDB authentication mechanism**
- **Authentication mechanism**: Choose an authentication mechanism for MongoDB. Use **SCRAM-SHA-256** for username/password authentication. Use **MONGODB-X509** for certificate-based authentication. For **MONGODB-X509**, you must configure the SSL keystore properties.
**How should we connect to your MongoDB database?**
- **Use secret manager**: Fetch sensitive configuration values from a secret manager.
**Secret manager configuration**
- **Secret manager**: Select the secret manager to use for retrieving sensitive data.
- **Configurations from Secret manager**: Select the configurations whose values Confluent Cloud
should fetch from the secret manager.
- **Provider Integration**: Select an existing provider integration that has access to your secret manager.
**MongoDB credentials**
- **Connection host**: The MongoDB host with connection string options. Use a hostname address and not a full
URL. For example, use `cluster4-r5q3r7.gcp.mongodb.net/?readPreference=secondary` for **MONGODB_ATLAS**
and `54.190.171.123:27017/?authSource=admin` for **MONGODB_SELF_MANAGED**.
#### NOTE
You don’t need to manually add the connection string parameters
`authMechanism=MONGODB-X509&authSource=$external` as part of the host. The connector
automatically includes the parameter when you select `MONGODB-X.509` as the authentication mechanism.
- **Connection user**: The MongoDB Atlas connection user.
- **Connection password**: The MongoDB Atlas connection password. When entering the password, make sure that any special characters are URL encoded.
**MongoDB Database Details**
- **Database name**: The MongoDB Atlas database name. If not set, all
databases in the cluster are watched.
- **Collection name**: Single MongoDB collection to watch. If not set, all
collections databases in the cluster are watched.
**SSL Configuration**
- **SSL keystore file**: Upload the **SSL keystore file** containing the server certificate and
enter the SSL keystore password used to access the keystore.
- **SSL keystore password**: Password used to access the keystore.
- **SSL truststore file**: Upload the **SSL truststore file** containing a server CA certificate and enter the
truststore SSL truststore password used to access the truststore.
- **SSL truststore password**: Password used to access the truststore.
2. Click **Continue**.
### Configuration
- **Output Kafka record value format**: Sets the output Kafka record value format. Valid entries are AVRO, JSON_SR, PROTOBUF, JSON, STRING or BSON. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO, JSON_SR, and PROTOBUF.
- **Output Kafka record key format**: Sets the output Kafka record key format. Valid entries are AVRO, JSON_SR, PROTOBUF, STRING or JSON. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO, JSON_SR, and PROTOBUF.
### **Show advanced configurations**
- **Schema context**: Select a schema context to use for this connector, if using
a schema-based data format. This property defaults to the **Default** context,
which configures the connector to use the default schema set up for Schema Registry in your
Confluent Cloud environment. A schema context allows you to use separate schemas (like
schema sub-registries) tied to topics in different Kafka clusters that share the
same Schema Registry environment. For example, if you select a non-default context, a
**Source** connector uses only that schema context to register a schema and a
**Sink** connector uses only that schema context to read from. For more
information about setting up a schema context, see [What are schema contexts and when should you use them?](../sr/faqs-cc.md#faq-schema-contexts).
- **Publish full document only**: Set whether to return only the
`fullDocument` field from the change stream event document
produced by any update event. The `fullDocument` field contains
the most current version of the updated document. Sets the
`change.stream.full.document=updateLookup` setting so updated
documents will be included.
- **Publish tombstone events on documents deletion**: When set to
`true`, the connector returns the tombstone events when
documents are deleted. Tombstone events contain the keys of
deleted documents with null values. This setting applies only when
`publish.full.document.only` is `true`.
- **Change stream full document**: Determines what to return for
update operations when using a Change Stream. The `default`
setting returns the differences between the original document and
the updated document. The `updateLookup` setting returns the
differences between the original document and updated document as
well as a copy of the entire updated document at a point in time
after the update. The `whenAvailable` setting returns the
updated document, if available. The `required` setting returns
the updated document and raises an error if it is not available.
- **Change stream full document before change**: Configures the
document pre-image your change stream returns on update
operations. The `default` setting suppresses the document
pre-image. When set to `whenAvailable` setting returns the
document pre-image if it’s available, before it was replaced,
updated, or deleted. The `required` setting returns the document
pre-image and raises an error if it is not available.
- **Use the \`\`documentKey\`\` for the source record key**: Use the document key as the source record key.
- **Show expanded events**: Determines if change streams notifies for DDL events, such as `createIndexes` and `dropIndexes` events. This functionality is new in version 6.0. See [MongoDB documentation](https://www.mongodb.com/docs/manual/reference/change-events/#std-label-change-streams-expanded-events) for more details on `showExpandedEvents`. This setting is required to show `updateDescription.disambiguatedPaths` in update events, helping clarify changes that involve ambiguous fields. This specific feature is new in version 6.1. See [MongoDB documentation](https://www.mongodb.com/docs/manual/reference/change-events/update/#path-disambiguation) for more details on `disambiguatedPaths`.
- **The collation options**: The JSON representation of the collation options to use for the change stream. Use the `Collation.asDocument().toJson()` to create the specific json representation.
- **Output json formatter**: The output format of json strings can be configured to be either: DefaultJson: The legacy strict json formatter. ExtendedJson: The fully type safe extended json formatter. SimplifiedJson: Simplified Json, with ObjectId, Decimals, Dates and Binary values represented as strings. Users can provide their own implementation of the com.mongodb.kafka.connect.source.json.formatter.
- **Topic separator**: A separator to use when the connector joins
prefix, database, collection, and suffix values. These joined values
form the Kafka topic name where data is published. Defaults to `.`.
- **Topic suffix**: A suffix to append to database and collection
names to generate the name of the Kafka topic the connector
creates.
- **Output schema infer value**: Whether the connector should infer the schema of the
`SourceRecord`. The connector processes each document in
isolation and may generate many schemas. This setting only
works with AVRO, JSON, JSON_SR, or PROTOBUF data formats.
When enabled, any schema pre-registered on the topic is not
used. For more information, see
[Schema FAQ](#cc-mongodb-source-schema-infer-faq).
- **Topic namespace map**: Add a JSON object that maps change stream
document namespaces to topics. For additional information, see
[Topic Namespace Map](https://www.mongodb.com/docs/kafka-connector/current/source-connector/usage-examples/topic-naming/#topic-namespace-map).
Multiple collections with records having varying schema are mapped
to a single topic for AVRO, JSON_SR, or PROTOBUF data formats.
These are registered to a single subject name. If the schemas are
not backward compatible, the connector fails until you change the
[schema compatibility](../sr/schemas-manage.md#cloud-schema-compat-mode) in
Confluent Cloud Schema Registry.
**Additional Configs**
- **Value Converter Replace Null With Default**: Specifies whether to replace fields that have a default value and that are null to the default value. When set to `true`, the connector uses the default value; otherwise, it uses `null`. Applies to the `JSON` converter.
- **Value Converter Reference Subject Name Strategy**: Sets the subject reference name strategy for values. Valid entries are `DefaultReferenceSubjectNameStrategy` or `QualifiedReferenceSubjectNameStrategy`. You can use this strategy only with `PROTOBUF` format; the default strategy is `DefaultReferenceSubjectNameStrategy`.
- **Value Converter Schemas Enable**: Includes schema within each of the serialized values. Input messages must contain `schema` and `payload` fields and must not contain additional fields. For plain `JSON` data, set this to `false`. Applies to the `JSON` converter.
- **Errors Tolerance**: Use this property to configure the connector’s error handling behavior.
#### WARNING
Use this property with caution for sink connectors, as it can lead to data loss. If you set this property to `all`, the connector does not fail on errant records, but logs them (and sends to DLQ for sink connectors) and continues processing. If you set this property to `none`, the connector task fails on errant records.
- **Value Converter Ignore Default For Nullables**: When set to `true`, this property ensures that the corresponding record in Kafka is `null`, instead of showing the default column value. Applies to the `AVRO`, `PROTOBUF`, and `JSON_SR` converters.
- **Value Converter Decimal Format**: Specifies the `JSON` or `JSON_SR` serialization format for Connect `DECIMAL` logical type values with two allowed literals:
`BASE64` to serialize `DECIMAL` logical types as base64 encoded binary data, and
`NUMERIC` to serialize `DECIMAL` logical type values in `JSON` or `JSON_SR` as a number representing the decimal value.
- **Key Converter Schema ID Serializer**: The class name of the schema ID serializer for keys. This is used to serialize schema IDs in the message headers.
- **Value Converter Connect Meta Data**: Enables the Connect converter to add its metadata to the output schema. Applies to Avro converters.
- **Value Converter Value Subject Name Strategy**: Determines how to construct the subject name under which the value schema is registered with Schema Registry.
- **Key Converter Key Subject Name Strategy**: Determines how to construct the subject name for key schema registration.
- **Value Converter Schema ID Serializer**: The class name of the schema ID serializer for values. This is used to serialize schema IDs in the message headers.
**Auto-restart policy**
- **Enable Connector Auto-restart**: Enables the auto-restart behavior of the connector and its
task in the event of user-actionable errors. Defaults to `true`, enabling the connector to
automatically restart in case of user-actionable errors. Set this property to `false` to
disable auto-restart for failed connectors. If disabled, you must manually restart the connector.
**Connection details**
- **Poll wait time (ms)**: The amount of time to wait before
checking for new results on the change stream.
- **Maximum documents to include in a batch**: The maximum number of
change stream documents to include in a single batch when polling
for new data.
- **Pipeline**: An array of JSON objects describing the pipeline
operations to filter or modify the change events output.
- **Startup mode**: Specifies how the connector starts up when
there is no source offset available. If no source offset is
available, the connector may either ignore all or some of the
existing source data, or it may first copy all existing source
data and then continue processing new data. When set to
`latest` (the default), the connector ignores all existing
source data. If set to `timestamp`, the connector actuates
startup.mode.timestamp.\* properties. If no properties are
configured, `timestamp` is equivalent to `latest`. If set to
`copy_existing`, the connector copies all existing source data
to Change Stream events. This setting is equivalent to the
deprecated setting `copy.existing=true`.
- **Copy existing namespace regex**: Regular expression that matches
the namespaces (`databaseName.collectionName`) from which to copy
data.
- **Copy existing pipeline**: An array of JSON objects describing
the pipeline operations to run when copying existing data. It will
only be applied for existing documents which are being copied.
- **Start timestamp**: Actuated only if `startup.mode=timestamp`.
Specifies the starting point for the change stream. Accepted
values can be an integer number of seconds since the Epoch in
decimal format (for example, `30`), or an instant in the
ISO-8601 format with one second precision (for example,
`1970-01-01T00:00:30Z`), or a BSON Timestamp in the canonical
extended JSON (v2) format (for example, `{"$timestamp": {"t": 30,
"i": 0}}`).
- **Cursor batch size**: The number of documents to return in a
batch. The value defaults to `0`. The maximum cursor batch size
is `50`.
- **Output Schema Key**: The Avro schema definition for the key value of the SourceRecord.
- **Output Schema Value**: The Avro schema definition for the value of the SourceRecord.
**Error handling**
- **Heartbeat interval**: The number of milliseconds the connector
waits between sending heartbeat messages.
- **Heartbeat topic name**: The name of the topic on which the
connector should publish heartbeat messages. You must provide a
positive value in the `heartbeat.interval.ms` setting to enable
this feature.
- **Remove field on schema mismatch**: If true, remove fields from the document that are not present in the schema. Otherwise, throw an error or send the documents to the DLQ depending on the value of errors.tolerance being set to ALL or NONE respectively.
- **Offset partition name**: The custom offset partition name to use.
Use this option to instruct the connector to start a new change
stream when an existing offset contains an invalid resume token. If
you leave this setting blank, the connector uses the default
partition name from the connection details.
**Error handling Mongo**
- **Error tolerance**: Allows you to customize how the connector
handles errors. By default, this is set to `NONE` and the
connector handles errors using the error handling tolerance
configured for the Connect framework.
- **Output errors**: Whether or not the connector sends output
conversion errors to the dead letter queue (DLQ). When using a
schema, this prevents unprocessable (poison) messages from
causing the connector task to fail. The connector outputs
messages to the DLQ as extended JSON for the specified topic.
Enabling this property requires that the **Error tolerance**
property be set to `all`. By default, the connector does not
output messages to the DLQ.
**Server API**
- **Server API version**: The MongoDB server API version to use.
This property is disabled by default.
- **Deprecation errors**: Whether or not to require the connector
to report the use of deprecated server APIs as errors. This
property is disabled by default.
- **Strict**: Sets whether the application requires strict server API version enforcement.
**Producer configuration**
- **Producer linger(ms)**: Artificial delay for records to be sent together.
#### NOTE
This connector doesn’t honor the `producer.override.linger.ms`
property and silently ignores any value you set for it. To
configure the producer linger time, use `linger.ms` directly
instead.
- **Producer batch size(bytes)**: Record batch size in bytes.
**Transforms**
- **Single Message Transformations**: To add a new SMT, see [Add transforms](single-message-transforms.md#cc-single-message-transforms-ui).
For more information about unsupported SMTs, see
[Unsupported transformations](single-message-transforms.md#cc-single-message-transforms-unsupported-transforms).
**Processing position**
- **Set offsets**: Click **Set offsets** to define a specific offset for
this connector to begin procession data from. For more information
on managing offsets, see [Manage offsets](offsets.md#connect-custom-offsets).
For all property values and definitions, see [Configuration Properties](#cc-mongodb-source-config-properties).
- Click **Continue**.
### Sizing
The connector supports running a single task.
Click **Continue**.
### Review and Launch
1. Verify the connection details by previewing the running configuration.
2. After you’ve validated that the properties are configured to your
satisfaction, click **Launch**.
The status for the connector should go from **Provisioning** to
**Running**.
#### Step 5: Check the Kafka topic
After the connector is running, verify that MongoDB documents are populating the
Kafka topic. If the config `startup.mode=copy_existing` and the connector
restarts due to any reason, you may see duplicate records in the topic.
For more information and examples to use with the Confluent Cloud API for Connect,
see the [Confluent Cloud API for Connect Usage Examples](connect-api-section.md#ccloud-connect-api) section.
### Using the Confluent CLI
Complete the following steps to set up and run the connector using the Confluent CLI.
#### NOTE
Make sure you have all your [prerequisites](#cc-mongo-db-source-prereqs) completed.
#### Step 1: List the available connectors
Enter the following command to list available connectors:
```none
confluent connect plugin list
```
#### Step 2: List the connector configuration properties
Enter the following command to show the connector configuration properties:
```none
confluent connect plugin describe
```
The command output shows the required and optional configuration properties.
#### Step 3: Create the connector configuration file
Create a JSON file that contains the connector configuration properties. The
following example shows the required connector properties.
```json
{
"connector.class": "MongoDbAtlasSource",
"name": "",
"kafka.auth.mode": "KAFKA_API_KEY",
"kafka.api.key": "",
"kafka.api.secret": "",
"topic.prefix": "",
"connection.host": "",
"connection.user": "",
"connection.password": "",
"database": "",
"collection": "",
"poll.await.time.ms": "5000",
"poll.max.batch.size": "1000",
"startup.mode": "copy_existing",
"output.data.format": "JSON",
"tasks.max": "1"
}
```
Note the following property definitions:
* `"connector.class"`: Identifies the connector plugin name.
* `"name"`: Sets a name for your new connector.
* `"kafka.auth.mode"`: Identifies the connector authentication mode you want to use. There are two options: `SERVICE_ACCOUNT` or `KAFKA_API_KEY` (the default). To use an API key and secret, specify the configuration properties `kafka.api.key` and `kafka.api.secret`, as shown in the example configuration (above). To use a [service account](service-account.md#s3-cloud-service-account), specify the **Resource ID** in the property `kafka.service.account.id=`. To list the available service account resource IDs, use the following command:
```bash
confluent iam service-account list
```
For example:
```bash
confluent iam service-account list
Id | Resource ID | Name | Description
+---------+-------------+-------------------+-------------------
123456 | sa-l1r23m | sa-1 | Service account 1
789101 | sa-l4d56p | sa-2 | Service account 2
```
* (Optional) `"topic.prefix"`: Enter a topic prefix. The connector
automatically creates Kafka topics using the naming convention:
`..`. The tables are created with
the properties: `topic.creation.default.partitions=1` and
`topic.creation.default.replication.factor=3`. If you want to create topics
with specific settings, create the topics before running this connector. Note
the following:
- If you are configuring granular access using a service account, you must set
up [ACLs for the topic prefix](service-account.md#cloud-service-account-jdbc-mongo-acls).
- If you are using a dedicated cluster and have a MongoDb document greater
than 2MB in size, create the topic beforehand with property
`max.message.bytes` set to match the largest document size or greater than
the largest document size (8388608 bytes maximum).
#### IMPORTANT
If you are configuring granular access using a [service account](service-account.md#s3-cloud-service-account), and you leave the optional **Topic prefix**
(`topic.prefix`) configuration property empty, you must grant ACL
`CREATE` and `WRITE` access to all the Kafka topics or create [RBAC
role bindings](managed-connector-rbac.md#managed-connector-rbac). To add ACLs, you use the (\*)
wildcard in the ACL entries as shown in the following examples.
```bash
confluent kafka acl create --allow --service-account
"" --operation create --topic "*"
```
```bash
confluent kafka acl create --allow --service-account
"" --operation write --topic "*"
```
* (Optional) `"topic.namespace.map"`: A JSON map that maps change stream document namespaces to topics. For example: `{\"db\": \"dbTopic\", \"db.coll\": \"dbCollTopic\"}` will map all change stream documents from the `db` database to `dbTopic.` apart from any documents from the `db.coll` namespace which map to the `dbCollTopic` topic. If you want to map all messages to a single topic use `*`. For example: `{\"*\": \"everyThingTopic\", \"db.coll\": \"exceptionToTheRuleTopic\"}` will map all change stream documents to the `everyThingTopic` apart from the `db.coll` messages. Note that any prefix configuration will still apply. If multiple collections with records having varying schema are mapped to a single topic with AVRO, JSON_SR, and PROTOBUF, then multiple schemas will be registered under a single subject name. If these schemas are not backward compatible to each other, the connector will fail until you change the schema compatibility in Confluent Cloud Schema Registry.
* `"connection.host"`: The MongoDB host with connection string options. Use a hostname address and not a full
URL. For example, use `cluster4-r5q3r7.gcp.mongodb.net/?readPreference=secondary` for MONGODB_ATLAS
and `54.190.171.123:27017/?authSource=admin` for MONGODB_SELF_MANAGED.
#### NOTE
* The connector does not support following connection string options in `connection.host`
config: `tlsCertificateKeyFile`, `tlsCertificateKeyFilePassword`, `tlsCAFile`,
`tlsAllowInvalidCertificates`, `tlsInsecure`, `tlsAllowInvalidHostnames`,
`authMechanism`, `authMechanismProperties`, `gssapiServiceName`.
* Other options like `readPreference`, `readConcernLevel`, or `w` defined in
[MongoDB Connection String Options](https://www.mongodb.com/docs/manual/reference/connection-string-options/#std-label-connections-connection-options)
can be configured in `connection.host` configuration. For example,
`cluster4-r5q3r7.gcp.mongodb.net/?readPreference=secondary&readConcernLevel=local&appName=test&w=majority`.
* The connector supports connecting to self-managed MongoDB database.
: Use `mongodb.instance.type` as MONGODB_SELF_MANAGED and specify the `connection.host` accordingly
to connect to self-managed instance. For example, `54.190.171.123:27017/?authSource=admin`.
* (Optional) `"collection"`: The collection name. If the property is not used, all collections are watched in the supplied database.
* (Optional) `"poll.await.time.ms"`: The amount of time to wait before checking for new results in the change stream. If not used, this property defaults to 5000 ms (5 seconds).
* (Optional) `"poll.max.batch.size"`: The maximum number of change stream documents to include in a single batch when polling for new data. This setting can be used to limit the amount of data buffered internally in the connector. If not used, this property defaults to 100 records.
* (Optional) `"pipeline"`: An array of JSON objects that represents the pipeline operations to filter or modify the change stream output. For example: `[{"$match": {"ns.coll": {"$regex": /^(collection1|collection2)$/}}}]` sets the connector to listen to the `collection1` and `collection2` collections only. If not used, this property defaults to an empty array.
* (Optional) `"startup.mode"`: Specifies how the connector should start up when there is no source offset available. Resuming a change stream requires a resume token, which the connector gets from the source offset. If no source offset is available, the connector may either ignore all or some of the existing source data, or may at first copy all existing source data and then continue with processing new data. When set to `latest` (default), the connector ignores all existing source data. If set to `timestamp`, the connector actuates startup.mode.timestamp.\* properties. If no properties are configured, `timestamp` is equivalent to `latest`. If `startup.mode=copy_existing`, the connector copies all existing source data to Change Stream events. This setting is equivalent to the deprecated setting `copy.existing=true`.
* (Optional) `"startup.mode.timestamp.start.at.operation.time"`: Actuated only if `startup.mode=timestamp`. Specifies the starting point for the change stream. Accepted values can be an integer number of seconds since the Epoch in decimal format (for example, `30`), or an instant in the ISO-8601 format with one second precision (for example, `1970-01-01T00:00:30Z`), or a BSON Timestamp in the canonical extended JSON (v2) format (for example, `{"$timestamp": {"t": 30, "i": 0}}`)
* (Optional) `"startup.mode.copy.existing.namespace.regex"`: Regex that matches the namespaces from which the existing documents are copied. A namespace is represented as `databaseName.collectionName`. For example, `stats\.page.*` matches all collections that start with `page` in the `stats` database.
* (Optional) `"startup.mode.copy.existing.pipeline"`: An array of JSON objects that describes the pipeline operations to run when copying existing data. It is applied to existing documents that are being copied. If not used, this property defaults to an empty array.
* (Optional) `"publish.full.document.only"`: Set whether to return only the `fullDocument` field from the change stream event document produced by any update event. The `fullDocument` field contains the most current version of the updated document. Sets the `change.stream.full.document=updateLookup` setting so updated documents will be included.
#### NOTE
This automatic configuration only occurs at the time of connector creation. Changing this setting while the connector is already running will not retroactively apply or update the `change.stream.full.document` behavior.
* (Optional) `"publish.full.document.only.tombstone.on.delete"`: When set to `true`, the connector returns the tombstone events when documents are deleted. Tombstone events contain the keys of deleted documents with null values. This setting applies only when `publish.full.document.only` is `true`.
* (Optional) `"change.stream.full.document"`: Determines what to return for update operations when using a Change Stream. The `default` setting returns the differences between the original document and the updated document. When set to `updateLookup` setting returns the differences between the original document and updated document as well as a copy of the entire updated document at a point in time after the update. The `whenAvailable` setting returns the updated document, if available. The `required` setting returns the updated document and raises an error if it is not available.
* (Optional) `"change.stream.full.document.before.change"`: Configures the document pre-image your change stream returns on update operations. The `default` setting suppresses the document pre-image. When set to `whenAvailable` setting returns the document pre-image if it’s available, before it was replaced, updated, or deleted. When set to `required` setting returns the document pre-image and raises an error if it is not available.
* `"output.data.format"`: Sets the output Kafka record value format (data
coming from the connector). Valid entries are `AVRO`, `JSON_SR`,
`PROTOBUF`, `JSON`, `STRING` or `BSON`. You must have Confluent Cloud Schema Registry
configured if using a schema-based message format (for example, Avro, JSON_SR
(JSON Schema), or Protobuf).
It chooses the appropriate converter and populates the derived settings `output.format.key` and `output.format.value` according to the table shown below.
| `output.data.format` | Converter | `output.format.key` | `output.format.value` |
|------------------------|---------------------|-----------------------|-------------------------|
| `AVRO` | AvroConverter | schema | schema |
| `JSON_SR` | JsonSchemaConverter | schema | schema |
| `PROTOBUF` | ProtobufConverter | schema | schema |
| `JSON` | JsonConverter | schema | schema |
| `STRING` | StringConverter | json | json |
| `BSON` | ByteArrayConverter | bson | bson |
If you select AVRO, be sure to set **Compatibility mode**
(`schema.compatibility.level`) to `NONE` in Schema Registry. Note that schemas are
generated per document in isolation. If not set to NONE, there is a chance
that the new schema generated for the new document will not be backward
compatible with previous versions of the schema.
* (Optional) `"heartbeat.interval.ms"`: The number of milliseconds the connector waits between sending heartbeat messages. If not used, this property defaults to 0. Thus, no heartbeat message is sent by default. If set to a positive number, the connector sends heartbeat messages when source records are not published in the specified interval. This mechanism improves resumability of the connector for low volume namespaces. See the **Invalid Resume Token** page in MongoDb documentation for more information on this feature. When using SMTs, use predicates to prevent SMTs from processing the heartbeat messages. For example, if the heartbeat topic name is `__mongodb_heartbeats` and the connector is writing the actual database records into topics that do not share common prefix with the heartbeat topic; use the following configuration to prevent heartbeat messages from being processed by the transform with an alias say, `mongoTransform`: `"predicates": "isHeartbeatTopicPrefix"`, `"predicates.isHeartbeatTopicPrefix.type": "org.apache.kafka.connect.transforms.predicates.TopicNameMatches"`, `"predicates.isHeartbeatTopicPrefix.pattern": "__mongodb.*"`, `"transforms.mongoTransform.predicate": "isHeartbeatTopicPrefix"`, `"transforms.mongoTransform.negate": "true"`.
* (Optional) `"heartbeat.topic.name"`: The name of the topic on which the connector should publish heartbeat messages. You must provide a positive value in the `heartbeat.interval.ms` setting to enable this feature. If setting the heartbeat messages for multiple connectors, you must ensure that the heartbeat topic names for the connectors are unique. If not set, this defaults to `__mongodb_heartbeats`.
* `"tasks.max"`: The connector supports running a single task.
**SMTs**: For details about adding SMTs using the Confluent CLI, see the [Single Message Transformations](single-message-transforms.md#cc-single-message-transforms) documentation.
See [Configuration Properties](#cc-mongodb-source-config-properties) for all property values and
definitions.
#### Step 4: Load the properties file and create the connector
Enter the following command to load the configuration and start the connector:
```none
confluent connect cluster create --config-file .json
```
For example:
```none
confluent connect cluster create --config-file mongo-db-source.json
```
Example output:
```none
Created connector confluent-mongodb-source lcc-ix4dl
```
#### Step 5: Check the connector status
Enter the following command to check the connector status:
```none
confluent connect cluster list
```
Example output:
```none
ID | Name | Status | Type
+-----------+---------------------------+---------+-------+
lcc-ix4dl | confluent-mongodb-source | RUNNING | source
```
#### Step 6: Check the Kafka topic.
After the connector is running, verify that MongoDB documents are populating the
Kafka topic. If the config `startup.mode=copy_existing` and the connector
restarts due to any reason, you may see duplicate records in the topic.
For more information and examples to use with the Confluent Cloud API for Connect,
see the [Confluent Cloud API for Connect Usage Examples](connect-api-section.md#ccloud-connect-api) section.
## Configuration Properties
Use the following configuration properties with the fully managed connector. For
self-managed connector property definitions and other details, see the connector
docs in [Self-managed connectors for Confluent Platform](/platform/current/connect/kafka_connectors.html).
### How should we connect to your data?
`name`
: Sets a name for your connector.
* Type: string
* Valid Values: A string at most 64 characters long
* Importance: high
### Kafka Cluster credentials
`kafka.auth.mode`
: Kafka Authentication mode. It can be one of KAFKA_API_KEY or SERVICE_ACCOUNT. It defaults to KAFKA_API_KEY mode, whenever possible.
* Type: string
* Valid Values: SERVICE_ACCOUNT, KAFKA_API_KEY
* Importance: high
`kafka.api.key`
: Kafka API Key. Required when kafka.auth.mode==KAFKA_API_KEY.
* Type: password
* Importance: high
`kafka.service.account.id`
: The Service Account that will be used to generate the API keys to communicate with Kafka Cluster.
* Type: string
* Importance: high
`kafka.api.secret`
: Secret associated with Kafka API key. Required when kafka.auth.mode==KAFKA_API_KEY.
* Type: password
* Importance: high
### Schema Config
`schema.context.name`
: Add a schema context name. A schema context represents an independent scope in Schema Registry. It is a separate sub-schema tied to topics in different Kafka clusters that share the same Schema Registry instance. If not used, the connector uses the default schema configured for Schema Registry in your Confluent Cloud environment.
* Type: string
* Default: default
* Importance: medium
### How do you want to name your topic(s)?
`topic.prefix`
: Prefix to prepend to table names to generate the name of the Apache Kafka® topic to publish data to.
* Type: string
* Importance: high
`topic.namespace.map`
: JSON object that maps change stream document namespaces to topics. Any prefix configuration will still apply. In case multiple collections with records having varying schema are mapped to single topic with AVRO, JSON_SR, and PROTOBUF, then multiple schemas will be registered under single subject name. If these schemas are not backward compatible to each other, the connector will fail until you change the schema compatibility in Confluent Cloud Schema Registry.
* Type: string
* Default: “”
* Importance: low
`topic.separator`
: Separator to use when joining prefix, database, collection, and suffix values. This generates the name of the Kafka topic to publish data to. Used by the ‘DefaultTopicMapper’.
* Type: string
* Default: .
* Importance: low
`topic.suffix`
: Suffix to append to database and collection names to generate the name of the Kafka topic to publish data to.
* Type: string
* Importance: low
### How should we connect to your MongoDB database?
`mongodb.instance.type`
: Specifies the type of MongoDB instance the connector will connect to.
* Type: string
* Default: MONGODB_ATLAS
* Valid Values: MONGODB_ATLAS, MONGODB_SELF_MANAGED
* Importance: high
`mongodb.auth.mechanism`
: Choose an authentication mechanism for MongoDB. Use SCRAM-SHA-256 for username/password authentication. Use MONGODB-X509 for certificate-based authentication. For MONGODB-X509, you must configure the SSL keystore properties.
* Type: string
* Default: SCRAM-SHA-256
* Valid Values: MONGODB-X509, SCRAM-SHA-256
* Importance: high
`secret.manager.enabled`
: Fetch sensitive configuration values from a secret manager.
* Type: boolean
* Default: false
* Importance: high
`connection.host`
: For MongoDB Atlas, provide the SRV connection host (e.g., mycluster.abc123.mongodb.net). For Self Managed MongoDB, provide the host and port in MongoDB URI format, e.g., host1:27017 or host1:27017/?replicaSet=myReplicaSet.
* Type: string
* Default: “”
* Importance: high
`connection.user`
: MongoDB connection user.
* Type: string
* Importance: high
`connection.password`
: MongoDB connection password.
* Type: password
* Importance: high
`connection.ssl.truststore.file`
: The trust store file containing trusted certificates. Supported formats include JKS and PKCS12. If not set, the default Java trust store is used.
* Type: password
* Default: [hidden]
* Importance: medium
`connection.ssl.truststorePassword`
: The password for the trust store file.
* Type: password
* Default: [hidden]
* Importance: medium
`connection.ssl.keystore.file`
: The key store file containing the client certificate and private key for MONGODB-X509 authentication. Supported formats include JKS and PKCS12.
* Type: password
* Default: [hidden]
* Importance: medium
`connection.ssl.keystorePassword`
: The password for the key store file. This is optional for the client and only needed if `connection.ssl.keystore.file` is configured.
* Type: password
* Default: [hidden]
* Importance: medium
`database`
: MongoDB database name.
* Type: string
* Importance: high
### Secret manager configuration
`secret.manager`
: Select the secret manager to use for retrieving sensitive data.
* Type: string
* Importance: high
`secret.manager.managed.configs`
: Select the configurations to fetch their values from the secret manager.
* Type: list
* Importance: high
`secret.manager.provider.integration.id`
: Select an existing provider integration that has access to your secret manager.
* Type: string
* Importance: high
### Database details
`collection`
: MongoDB collection name.
* Type: string
* Importance: medium
### Connection details
`poll.await.time.ms`
: The amount of time to wait before checking for new results on the change stream.
* Type: int
* Default: 5000 (5 seconds)
* Valid Values: [1,…]
* Importance: low
`poll.max.batch.size`
: Maximum number of change stream documents to include in a single batch when polling for new data. This setting can be used to limit the amount of data buffered internally in the connector.
* Type: int
* Default: 100
* Valid Values: [1,…,1000]
* Importance: low
`pipeline`
: An array of JSON objects describing the pipeline operations to filter or modify the change events output. For example, [{“$match”: {“ns.coll”: {“$regex”: /^(collection1|collection2)$/}}}] will set your source connector to listen to the “collection1” and “collection2” collections only.
* Type: string
* Default: []
* Importance: medium
`startup.mode`
: Specifies how the connector should start up when there is no source offset available. If set to ‘latest’, the connector ignores all existing source data. If set to ‘timestamp’, the connector actuates startup.mode.timestamp.\* properties. If no properties are configured, timestamp is equivalent to latest. If startup.mode=copy_existing, the connector copies all existing source data to Change Stream events.
* Type: string
* Default: “”
* Importance: high
`startup.mode.copy.existing.namespace.regex`
: Regular expression that matches the namespaces (databaseName.collectionName) from which to copy data. For example, stats.page.\* matches all collections that starts with “page” in “stats” database.
* Type: string
* Default: “”
* Importance: medium
`startup.mode.copy.existing.pipeline`
: An array of JSON objects describing the pipeline operations to run when copying existing data. It will only be applied for existing documents which are being copied.
* Type: string
* Default: “”
* Importance: medium
`startup.mode.timestamp.start.at.operation.time`
: Actuated only if startup.mode=timestamp. Specifies the starting point for the change stream.
* Type: string
* Default: “”
* Importance: medium
`batch.size`
: The number of documents to return in a batch.
* Type: int
* Default: 0
* Valid Values: […,50]
* Importance: low
`output.schema.key`
: The Avro schema definition for the key value of the SourceRecord.
* Type: string
* Default: { “type”: “record”, “name”: “keySchema”, “fields”: [{ “name”: “_id”, “type”: “string”}]}
* Valid Values: A string at most 100000 characters long
* Importance: medium
`output.schema.value`
: The Avro schema definition for the value of the SourceRecord.
* Type: string
* Default: {“name”: “ChangeStream”, “type”: “record”, “fields”: [{“name”: “_id”, “type”: “string”}, {“name”: “operationType”, “type”: [“string”, “null”]}, {“name”: “fullDocumentBeforeChange”, “type”: [“string”, “null”]}, {“name”: “fullDocument”, “type”: [“string”, “null”]}, {“name”: “ns”, “type”: [{“name”: “ns”, “type”: “record”, “fields”: [{“name”: “db”, “type”: “string”}, {“name”: “coll”, “type”: [“string”, “null”]}]}, “null”]}, {“name”: “to”, “type”: [{“name”: “to”, “type”: “record”, “fields”: [{“name”: “db”, “type”: “string”}, {“name”: “coll”, “type”: [“string”, “null”]}]}, “null”]}, {“name”: “documentKey”, “type”: [“string”, “null”]}, {“name”: “updateDescription”, “type”: [{“name”: “updateDescription”, “type”: “record”, “fields”: [{“name”: “updatedFields”, “type”: [“string”, “null”]}, {“name”: “removedFields”, “type”: [{“type”: “array”, “items”: “string”}, “null”]}]}, “null”]}, {“name”: “clusterTime”, “type”: [“string”, “null”]}, {“name”: “txnNumber”, “type”: [“long”, “null”]}, {“name”: “lsid”, “type”: [{“name”: “lsid”, “type”: “record”, “fields”: [{“name”: “id”, “type”: “string”}, {“name”: “uid”, “type”: “string”}]}, “null”]}]}
* Valid Values: A string at most 100000 characters long
* Importance: medium
### Producer configuration
`linger.ms`
: Artificial delay for records to be sent together. Note that this connector doesn’t honor the `producer.override.linger.ms` property and silently ignores any value you set for it. To configure the producer linger time, use `linger.ms` directly instead.
* Type: long
* Default: 0
* Valid Values: [0,…,20000]
* Importance: medium
`producer.batch.size`
: Record batch size in bytes.
* Type: int
* Default: 16384
* Valid Values: [0,…,491520]
* Importance: medium
### Output messages
`output.data.format`
: Sets the output Kafka record value format. Valid entries are AVRO, JSON_SR, PROTOBUF, JSON, STRING or BSON. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO, JSON_SR, and PROTOBUF
* Type: string
* Default: STRING
* Importance: high
`output.key.format`
: Sets the output Kafka record key format. Valid entries are AVRO, JSON_SR, PROTOBUF, STRING or JSON. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO, JSON_SR, and PROTOBUF
* Type: string
* Default: STRING
* Valid Values: AVRO, JSON, JSON_SR, PROTOBUF, STRING
* Importance: high
`publish.full.document.only`
: Only publish the changed document instead of the full change stream document. Sets the change.stream.full.document=updateLookup automatically so updated documents will be included.
* Type: boolean
* Default: false
* Importance: high
`publish.full.document.only.tombstone.on.delete`
: Return the tombstone events when documents are deleted. Tombstone events contain the keys of deleted documents with null values. This setting applies only when publish.full.document.only is true
* Type: boolean
* Default: false
* Importance: high
`change.stream.full.document`
: Determines what to return for update operations when using a Change Stream. When set to ‘updateLookup’ setting returns the differences between the original document and updated document as well as a copy of the entire updated document at a point in time after the update. The ‘whenAvailable’ setting returns the updated document, if available. The ‘required’ setting returns the updated document and raises an error if it is not available.
* Type: string
* Default: default
* Importance: high
`change.stream.full.document.before.change`
: Configures the document pre-image your change stream returns on update operations. When set to ‘whenAvailable’ setting returns the document pre-image if it’s available, before it was replaced, updated, or deleted. When set to ‘required’ setting returns the document pre-image and raises an error if it is not available.
* Type: string
* Default: default
* Importance: high
`change.stream.document.key.as.key`
: Use the document key as the source record key.
* Type: boolean
* Default: false
* Importance: medium
`change.stream.show.expanded.events`
: Determines if change streams notifies for DDL events, such as `createIndexes` and `dropIndexes` events. This functionality is new in version 6.0. See [MongoDB documentation](https://www.mongodb.com/docs/manual/reference/change-events/#std-label-change-streams-expanded-events) for more details on `showExpandedEvents`. This setting is required to show `updateDescription.disambiguatedPaths` in update events, helping clarify changes that involve ambiguous fields. This specific feature is new in version 6.1. See [MongoDB documentation](https://www.mongodb.com/docs/manual/reference/change-events/update/#path-disambiguation) for more details on `disambiguatedPaths`.
* Type: boolean
* Default: false
* Importance: medium
`collation`
: The JSON representation of the collation options to use for the change stream. Use the `Collation.asDocument().toJson()` to create the specific json representation.
* Type: string
* Default: “”
* Importance: high
`output.json.format`
: The output format of json strings can be configured to be either: DefaultJson: The legacy strict json formatter. ExtendedJson: The fully type safe extended json formatter. SimplifiedJson: Simplified Json, with ObjectId, Decimals, Dates and Binary values represented as strings. Users can provide their own implementation of the com.mongodb.kafka.connect.source.json.formatter.
* Type: string
* Default: DefaultJson
* Importance: high
`output.schema.infer.value`
: Whether the connector should infer the schema for the value document of the Source Record. Since the connector processes each document in isolation, the connector may generate many schemas. The connector only reads this setting when you set your ‘Output Kafka record value format’ setting to AVRO, JSON, JSON_SR and PROTOBUF.
* Type: boolean
* Default: true
* Importance: low
### Error handling
`heartbeat.interval.ms`
: The number of milliseconds the connector waits between sending heartbeat messages. The connector sends heartbeat messages when source records are not published in the specified interval. This mechanism improves resumability of the connector for low volume namespaces. When using SMTs, use predicates to prevent SMTs from processing the heartbeat messages. See connector documentation for more details.
* Type: int
* Default: 0
* Importance: medium
`heartbeat.topic.name`
: The name of the topic on which the connector should publish heartbeat messages. You must provide a positive value in the “heartbeat.interval.ms” setting to enable this feature.
* Type: string
* Default: \_\_mongodb_heartbeats
* Importance: medium
`remove.field.on.schema.mismatch`
: If true, remove fields from the document that are not present in the schema. Otherwise, throw an error or send the documents to the DLQ depending on the value of errors.tolerance being set to ALL or NONE respectively.
* Type: boolean
* Default: true
* Importance: medium
`mongo.errors.tolerance`
: Use this property if you would like to configure the connector’s error handling behavior differently from the Connect framework’s.
* Type: string
* Default: NONE
* Importance: medium
`mongo.errors.deadletterqueue.topic.name`
: Whether to output conversion errors to the dead letter queue. Stops poison messages when using schemas, any message will be outputted as extended json on the specified topic. By default messages are not outputted to the dead letter queue. Also requires errors.tolerance=all.
* Type: string
* Importance: medium
`offset.partition.name`
: The custom offset partition name to use. You can use this option to instruct the connector to start a new change stream when an existing offset contains an invalid resume token. If you leave this setting blank, the connector uses the default partition name based on the connection details.
* Type: string
* Default: “”
* Importance: medium
### Server API
`server.api.version`
: The server API version to use. Disabled by default.
* Type: string
* Importance: low
`server.api.deprecation.errors`
: Sets whether the connector requires use of deprecated server APIs to be reported as errors.
* Type: boolean
* Default: false
* Importance: low
`server.api.strict`
: Sets whether the application requires strict server API version enforcement.
* Type: boolean
* Default: false
* Importance: low
### Number of tasks for this connector
`tasks.max`
: Maximum number of tasks for the connector.
* Type: int
* Valid Values: [1,…,1]
* Importance: high
### Additional Configs
`header.converter`
: The converter class for the headers. This is used to serialize and deserialize the headers of the messages.
* Type: string
* Importance: low
`producer.override.compression.type`
: The compression type for all data generated by the producer. Valid values are none, gzip, snappy, lz4, and zstd.
* Type: string
* Importance: low
`producer.override.linger.ms`
: The producer groups together any records that arrive in between request transmissions into a single batched request. More details can be found in the documentation: [https://docs.confluent.io/platform/current/installation/configuration/producer-configs.html#linger-ms](https://docs.confluent.io/platform/current/installation/configuration/producer-configs.html#linger-ms).
* Type: long
* Valid Values: [100,…,1000]
* Importance: low
`value.converter.allow.optional.map.keys`
: Allow optional string map key when converting from Connect Schema to Avro Schema. Applicable for Avro Converters.
* Type: boolean
* Importance: low
`value.converter.auto.register.schemas`
: Specify if the Serializer should attempt to register the Schema.
* Type: boolean
* Importance: low
`value.converter.connect.meta.data`
: Allow the Connect converter to add its metadata to the output schema. Applicable for Avro Converters.
* Type: boolean
* Importance: low
`value.converter.enhanced.avro.schema.support`
: Enable enhanced schema support to preserve package information and Enums. Applicable for Avro Converters.
* Type: boolean
* Importance: low
`value.converter.enhanced.protobuf.schema.support`
: Enable enhanced schema support to preserve package information. Applicable for Protobuf Converters.
* Type: boolean
* Importance: low
`value.converter.flatten.unions`
: Whether to flatten unions (oneofs). Applicable for Protobuf Converters.
* Type: boolean
* Importance: low
`value.converter.generate.index.for.unions`
: Whether to generate an index suffix for unions. Applicable for Protobuf Converters.
* Type: boolean
* Importance: low
`value.converter.generate.struct.for.nulls`
: Whether to generate a struct variable for null values. Applicable for Protobuf Converters.
* Type: boolean
* Importance: low
`value.converter.int.for.enums`
: Whether to represent enums as integers. Applicable for Protobuf Converters.
* Type: boolean
* Importance: low
`value.converter.latest.compatibility.strict`
: Verify latest subject version is backward compatible when use.latest.version is true.
* Type: boolean
* Importance: low
`value.converter.object.additional.properties`
: Whether to allow additional properties for object schemas. Applicable for JSON_SR Converters.
* Type: boolean
* Importance: low
`value.converter.optional.for.nullables`
: Whether nullable fields should be specified with an optional label. Applicable for Protobuf Converters.
* Type: boolean
* Importance: low
`value.converter.optional.for.proto2`
: Whether proto2 optionals are supported. Applicable for Protobuf Converters.
* Type: boolean
* Importance: low
`value.converter.scrub.invalid.names`
: Whether to scrub invalid names by replacing invalid characters with valid characters. Applicable for Avro and Protobuf Converters.
* Type: boolean
* Importance: low
`value.converter.use.latest.version`
: Use latest version of schema in subject for serialization when auto.register.schemas is false.
* Type: boolean
* Importance: low
`value.converter.use.optional.for.nonrequired`
: Whether to set non-required properties to be optional. Applicable for JSON_SR Converters.
* Type: boolean
* Importance: low
`value.converter.wrapper.for.nullables`
: Whether nullable fields should use primitive wrapper messages. Applicable for Protobuf Converters.
* Type: boolean
* Importance: low
`value.converter.wrapper.for.raw.primitives`
: Whether a wrapper message should be interpreted as a raw primitive at root level. Applicable for Protobuf Converters.
* Type: boolean
* Importance: low
`errors.tolerance`
: Use this property if you would like to configure the connector’s error handling behavior. WARNING: This property should be used with CAUTION for SOURCE CONNECTORS as it may lead to dataloss. If you set this property to ‘all’, the connector will not fail on errant records, but will instead log them (and send to DLQ for Sink Connectors) and continue processing. If you set this property to ‘none’, the connector task will fail on errant records.
* Type: string
* Default: none
* Importance: low
`key.converter.key.schema.id.serializer`
: The class name of the schema ID serializer for keys. This is used to serialize schema IDs in the message headers.
* Type: string
* Default: io.confluent.kafka.serializers.schema.id.PrefixSchemaIdSerializer
* Importance: low
`key.converter.key.subject.name.strategy`
: How to construct the subject name for key schema registration.
* Type: string
* Default: TopicNameStrategy
* Importance: low
`key.converter.replace.null.with.default`
: Whether to replace fields that have a default value and that are null to the default value. When set to true, the default value is used, otherwise null is used. Applicable for JSON Key Converter.
* Type: boolean
* Default: true
* Importance: low
`key.converter.schemas.enable`
: Include schemas within each of the serialized keys. Input message keys must contain schema and payload fields and may not contain additional fields. For plain JSON data, set this to false. Applicable for JSON Key Converter.
* Type: boolean
* Default: false
* Importance: low
`value.converter.decimal.format`
: Specify the JSON/JSON_SR serialization format for Connect DECIMAL logical type values with two allowed literals:
BASE64 to serialize DECIMAL logical types as base64 encoded binary data and
NUMERIC to serialize Connect DECIMAL logical type values in JSON/JSON_SR as a number representing the decimal value.
* Type: string
* Default: BASE64
* Importance: low
`value.converter.flatten.singleton.unions`
: Whether to flatten singleton unions. Applicable for Avro and JSON_SR Converters.
* Type: boolean
* Default: false
* Importance: low
`value.converter.ignore.default.for.nullables`
: When set to true, this property ensures that the corresponding record in Kafka is NULL, instead of showing the default column value. Applicable for AVRO,PROTOBUF and JSON_SR Converters.
* Type: boolean
* Default: false
* Importance: low
`value.converter.reference.subject.name.strategy`
: Set the subject reference name strategy for value. Valid entries are DefaultReferenceSubjectNameStrategy or QualifiedReferenceSubjectNameStrategy. Note that the subject reference name strategy can be selected only for PROTOBUF format with the default strategy being DefaultReferenceSubjectNameStrategy.
* Type: string
* Default: DefaultReferenceSubjectNameStrategy
* Importance: low
`value.converter.replace.null.with.default`
: Whether to replace fields that have a default value and that are null to the default value. When set to true, the default value is used, otherwise null is used. Applicable for JSON Converter.
* Type: boolean
* Default: true
* Importance: low
`value.converter.schemas.enable`
: Include schemas within each of the serialized values. Input messages must contain schema and payload fields and may not contain additional fields. For plain JSON data, set this to false. Applicable for JSON Converter.
* Type: boolean
* Default: false
* Importance: low
`value.converter.value.schema.id.serializer`
: The class name of the schema ID serializer for values. This is used to serialize schema IDs in the message headers.
* Type: string
* Default: io.confluent.kafka.serializers.schema.id.PrefixSchemaIdSerializer
* Importance: low
`value.converter.value.subject.name.strategy`
: Determines how to construct the subject name under which the value schema is registered with Schema Registry.
* Type: string
* Default: TopicNameStrategy
* Importance: low
### Auto-restart policy
`auto.restart.on.user.error`
: Enable connector to automatically restart on user-actionable errors.
* Type: boolean
* Default: true
* Importance: medium
## Suggested Reading
Blog post: [Using the Fully Managed MongoDB Atlas Connector in a Secure Environment](https://www.confluent.io/blog/mongodb-atlas-connector-in-secure-environments/)
Blog post: [Announcing the MongoDB Atlas Sink and Source connectors in Confluent Cloud](https://www.confluent.io/blog/confluent-cloud-offers-kafka-mongodb-connector-managed-clusters/)
## Frequently asked questions
Find answers to frequently asked questions about the MongoDB Atlas Source connector for Confluent Cloud.
### Why is my connector stuck in `PROVISIONING` state?
If your connector remains in `PROVISIONING` state indefinitely without transitioning to `RUNNING`, this indicates the connector failed to complete the deployment process.
Common causes and solutions:
* **Invalid MongoDB credentials**: Verify your MongoDB connection host, username, and password are correctly configured. Test your credentials using a MongoDB client before configuring the connector.
* **Connection host format**: Use the correct connection host format. For `MONGODB_ATLAS`, use a service record such as `cluster4-r5q3r7.gcp.mongodb.net`. For `MONGODB_SELF_MANAGED`, use a standard connection string such as `54.190.171.123:27017`.
* **Network connectivity**: Ensure the connector can reach your MongoDB instance. If your MongoDB instance is not publicly accessible, verify that you have added all Confluent Cloud egress IP addresses to your MongoDB IP whitelist. For more information, see [Public Egress IP Addresses for Confluent Cloud Connectors](static-egress-ip.md#cc-static-egress-ips).
* **Insufficient privileges**: Verify the database user has been granted either the `readWrite` role, or both the `readAnyDatabase` and `clusterMonitor` roles. For more information, see [Prerequisites](https://www.mongodb.com/docs/kafka-connector/current/introduction/connect/#prerequisites).
* **Invalid database or collection**: Verify the database and collection specified in the configuration exist and are accessible.
If the connector remains stuck after verifying these settings, delete and recreate the connector with the corrected configuration.
### Why does my connector fail with authentication errors?
Authentication errors occur when the connector cannot authenticate with your MongoDB instance.
Common causes and solutions:
* **Incorrect credentials**: Verify your MongoDB username and password are correct. Test authentication using a MongoDB client to confirm credentials work.
* **X.509 certificate issues**: If you use X.509 certificate authentication, ensure your certificate and private key are correctly formatted. The certificate should include the full chain and the private key should be in PEM format without a passphrase.
* **Authentication source**: For `MONGODB_SELF_MANAGED` deployments, you may need to specify the `authSource` parameter in the connection host. For example: `54.190.171.123:27017/?authSource=admin`.
* **Connection string format**: Do not include the username and password in the connection host string. Instead, provide them in the separate `connection.user` and `connection.password` fields.
For X.509 authentication setup, see [connector authentication](#cc-mongo-db-source-setup-connection).
### Why am I seeing duplicate records when the connector restarts?
Duplicate records can occur when you use `startup.mode=copy_existing` and the connector restarts.
Common causes and solutions:
* **Copy existing behavior**: When you set `startup.mode` to `copy_existing`, the connector first copies all existing source data as Change Stream events, then continues with processing new data. If the connector restarts during the copy phase, it may reprocess some documents that were already copied.
* **Expected behavior for at-least-once delivery**: The connector guarantees at-least-once delivery semantics. This means some duplicate records may occur during failures or restarts. Implement deduplication logic in your consumer applications based on document `_id` or other unique identifiers.
* **Resume token expiration**: If you stop the connector for an extended period, the resume token may expire. When the connector restarts, it will start from the beginning based on `startup.mode`, which can result in duplicates.
To minimize duplicates, avoid restarting the connector during the initial copy phase and implement idempotent consumer logic.
### Why does my connector fail with `invalid resume token` errors?
This error occurs when the connector attempts to resume a change stream with a token that is no longer in the MongoDB oplog.
Error example:
```none
ChangeStreamHistoryLost: PlanExecutor error during aggregation :: Resume of change stream
was not possible, as the resume point may no longer be in the oplog
```
Common causes:
* **Connector stopped too long**: If the connector is stopped for longer than the MongoDB oplog retention period, the resume token saved at shutdown becomes invalid. MongoDB Atlas retains oplog entries for a limited time based on your cluster tier and configuration.
* **Low-volume collection with no recent activity**: For collections that receive infrequent writes, the connector may not commit a fresh resume token often enough while running. As the oplog advances with activity from other collections, the saved token can fall outside the retention window before the connector commits an updated position.
To recover from this error:
1. Pause or stop the connector.
2. Delete the connector offsets using the Offsets API. This resets the connector to its base state, as if it were newly created. For more information, see [Manage custom offsets](#cc-mongodb-source-custom-offsets).
Alternatively, if you have a known valid resume token, use the `PATCH` operation on the Offsets API to resume from that specific position rather than performing a full reset.
3. Update `startup.mode` in the connector configuration if the current value does not match your recovery requirements. For example, set to `latest` to skip existing data and resume from the current position, or `copy_existing` to reprocess all existing documents from the beginning.
4. Restart the connector to begin from the configured startup position.
To prevent this error for low-volume collections, set `heartbeat.interval.ms` to a positive value. When enabled, the connector periodically commits its latest resume token even when no data changes occur in the watched collection, keeping the saved token within the oplog retention window. Heartbeats only help while the connector is running — they do not protect against token expiry when the connector is stopped.
### How do I configure the connector to filter specific collections?
You can filter collections using the `pipeline` configuration property.
The `pipeline` property accepts an array of JSON objects representing MongoDB aggregation pipeline operations. For example:
```none
"pipeline": "[{\"$match\": {\"ns.coll\": {\"$regex\": /^(orders|customers)$/}}}]"
```
This configuration filters the change stream to only include documents from the `orders` and `customers` collections.
Additional filtering options:
* **Filter by operation type**: Use `"pipeline": "[{\"$match\": {\"operationType\": \"insert\"}}]"` to only capture insert operations.
* **Filter by field values**: Combine multiple match conditions to filter based on document field values.
* **Collection property**: Use the `collection` property to watch a single collection. If you do not specify a collection, the connector watches all collections in the database.
For more information about pipeline syntax, see the MongoDB documentation on [Aggregation Pipeline](https://docs.mongodb.com/manual/core/aggregation-pipeline/).
### How do I map MongoDB collections to custom Kafka topic names?
Use the `topic.namespace.map` property to map change stream document namespaces to custom topic names.
Example configuration:
```none
"topic.namespace.map": "{\"mydb.orders\": \"kafka-orders\", \"mydb.customers\": \"kafka-customers\"}"
```
This maps the `mydb.orders` collection to the `kafka-orders` topic and `mydb.customers` to `kafka-customers`.
Important considerations:
* **Wildcard mapping**: Use `*` to map all collections to a single topic. For example: `"{\"*\": \"allEvents\", \"mydb.orders\": \"ordersOnly\"}"` maps all collections except `mydb.orders` to the `allEvents` topic.
* **Prefix still applies**: The `topic.prefix` setting applies to all mapped topic names.
* **Schema compatibility**: If you map multiple collections with different schemas to a single topic using `AVRO`, `JSON_SR`, or `PROTOBUF`, ensure schemas are backward compatible or change the schema compatibility mode in Confluent Cloud Schema Registry to `NONE`.
For more information, see the `topic.namespace.map` property in [Configuration Properties](#cc-mongodb-source-config-properties).
### Why does my connector fail with schema compatibility errors when using `AVRO`?
Schema compatibility errors occur when new document schemas are not compatible with previously registered schemas in Confluent Cloud Schema Registry.
Error example:
```none
Schema being registered is incompatible with an earlier schema
```
Common causes and solutions:
* **Varying document structures**: MongoDB is schema-flexible, allowing documents in the same collection to have different structures. Each unique document structure generates a new schema, which may not be backward compatible with existing schemas.
* **Schema compatibility mode**: Set the Confluent Cloud Schema Registry compatibility mode to `NONE` for the connector’s subject. This allows incompatible schemas to be registered. This may impact downstream consumers that expect strict schema compatibility.
* **Use JSON format**: Consider using `JSON` output format instead of `AVRO` if your documents have highly variable structures. JSON format does not require schema registration.
To change schema compatibility mode:
1. Navigate to Confluent Cloud Schema Registry in the Confluent Cloud Console.
2. Find the subject for your connector topic.
3. Change the compatibility mode to `NONE`.
For more information, see [Schema Registry compatibility types](../sr/fundamentals/schema-evolution.md#sr-compatibility-types).
### Why is my connector generating many schemas when `output.schema.infer.value` is enabled?
When `output.schema.infer.value` is set to `true`, the connector infers
the schema from each incoming MongoDB document independently. Because MongoDB
is schema-flexible, documents with different structures generate distinct
schemas, which can result in a large number of schema versions registered in
Confluent Cloud Schema Registry.
Additionally, any schema pre-registered on the topic isn’t used when schema
inference is enabled. The connector infers schemas directly from incoming
documents regardless of what’s registered on the topic.
To address this, use one of the following options:
* **Disable schema inference**: Set `output.schema.infer.value` to
`false` and create separate connectors per collection. Use
`output.schema.value` to specify a fixed schema for each collection so
the connector doesn’t generate new schemas per document.
* **Allow multiple schemas with no compatibility checks**: Keep
`output.schema.infer.value` set to `true`, don’t pre-register schemas
on the topic, and set the Confluent Cloud Schema Registry compatibility mode to `NONE` for
the connector’s subjects. Be aware that disabling compatibility checks may
affect downstream consumers that expect consistent schemas.
* **Use STRING or JSON output format**: Set `output.data.format` to
`STRING` or `JSON`. The `output.schema.infer.value` setting is
ignored for these formats because schema registration only applies to
`AVRO`, `JSON_SR`, and `PROTOBUF`.
### What should I set for the `poll.await.time.ms` and `poll.max.batch.size` properties?
These properties control how the connector polls for changes from MongoDB.
* **poll.await.time.ms**: The amount of time to wait before checking for new results in the change stream. Default is `5000` ms. Lower values reduce latency but increase polling frequency. Higher values reduce polling frequency for low-volume collections.
* **poll.max.batch.size**: The maximum number of change stream documents to include in a single batch. Default is `100`. Lower this value if you experience connector memory issues.
Monitor your connector’s throughput and adjust these values based on your specific workload requirements.
### How do I handle connection string options for MongoDB?
Specify connection string options in the `connection.host` property.
For `MONGODB_ATLAS`, use the format:
```none
cluster4-r5q3r7.gcp.mongodb.net/?readPreference=secondary&readConcernLevel=local
```
For `MONGODB_SELF_MANAGED`, use the format:
```none
54.190.171.123:27017/?authSource=admin&readPreference=primary
```
Important considerations:
* **Do not include protocol**: Do not include `mongodb://` or `mongodb+srv://` in the connection host.
* **Do not include credentials**: Do not include username and password in the connection string. Use the separate `connection.user` and `connection.password` fields.
* **Supported options**: Not all MongoDB connection string options are supported. For the list of unsupported options, see the connector documentation.
For more information about connection string options, see [MongoDB Connection String Options](https://www.mongodb.com/docs/manual/reference/connection-string-options/).
## Next Steps
For an example that shows fully managed Confluent Cloud connectors in action with
Confluent Cloud for Apache Flink, see the [Cloud ETL Demo](/platform/current/tutorials/examples/cloud-etl/docs/index.html).
This example also shows how to use Confluent CLI to manage your resources in
Confluent Cloud.
[](https://docs.confluent.io/platform/current/tutorials/examples/cloud-etl/docs/index.html)