Neo4j Sink Connector for Confluent Cloud
The fully-managed Neo4j Sink connector moves data from Apache Kafka® to Neo4j and Aura databases. The connector uses multiple write strategies, such as Cypher, Change Data Capture (CDC), Pattern, and Create-Update-Delete (CUD).
Note
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.
Features
The Neo4j Sink connector supports the following features:
Real-time data delivery: Delivers records from Kafka topics to Neo4j in near real time, enabling continuous data synchronization.
Flexible data mapping: Maps Kafka record values (including Avro and JSON) to nodes and relationships in Neo4j using Cypher or Pattern strategy defined in the configuration.
Schema handling: Supports both schema-less records (for example, JSON) and records with schemas (for example, Avro), allowing the connector to adapt to various data structures.
Error handling: Provides robust resilience and error handling, including support for a Dead Letter Queue (DLQ) to store records that fail processing.
Data type conversion: Supports conversion between built-in Kafka Connect types and Neo4j data types.
Secure authentication: Supports secure authentication for connecting to your Neo4j database using NONE, BASIC, KERBEROS, BEARER, and CUSTOM authentication types.
For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.
Limitations
Be sure to review the following information.
For connector limitations, see Neo4j Sink Connector limitations.
If you plan to use one or more Single Message Transforms (SMTs), see SMT Limitations.
If you plan to use Confluent Cloud Schema Registry, see Schema Registry Enabled Environments.
Quick Start
Use this quick start to get up and running with the Confluent Cloud Neo4j Sink connector. The quick start provides the basics of selecting the connector and configuring it to stream Kafka events to a Neo4j database.
- Prerequisites
Authorized access to a Confluent Cloud cluster on Amazon Web Services (AWS), Microsoft Azure (Azure), or Google Cloud.
The Confluent CLI installed and configured for the cluster. For more information, see Install the Confluent CLI.
Schema Registry must be enabled to use a Schema Registry-based format (for example, AVRO, JSON_SR (JSON Schema), or PROTOBUF). For more information, see Schema Registry Enabled Environments.
Access to a Couchbase database.
For networking considerations, see Networking and DNS. To use a set of public egress IP addresses, see Public Egress IP Addresses for Confluent Cloud Connectors.
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.
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 Neo4j Sink connector card.

Step 4: Enter the connector details
Note
Ensure you have all your prerequisites completed.
An asterisk ( * ) designates a required entry.
At the Add Neo4j Sink Connector screen, complete the following:
If you’ve already populated your Kafka topics, select the topics you want to connect from the Topics list.
To create a new topic, click +Add new topic.
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. 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.
Click Continue.
Connection
Neo4j URI: The Neo4j endpoint URL. For example,
neo4j+s://xxxx.databases.neo4j.io. You can specify multiple URIs separated by a comma (,).Database Name: The name of your Neo4j database.
Authentication Type: Under Authentication Type, select how you want to authenticate with the database:
If you select BASIC, enter the following details:
Username: The name of the Neo4j database user connecting to the Neo4j database.
Password: The password for the Neo4j database user connecting to the Neo4j database.
Authentication Realm: The authentication realm to authenticate with. Leave this field empty to use the default realm.
If you select BEARER, enter the BEARER Token.
If you select CUSTOM, enter the following details:
Custom Authentication Scheme: The custom authentication scheme used to establish the connection.
Custom Principal: The custom principal used to establish the connection.
Custom Credentials: The custom credential used to establish the connection.
Custom Authentication Realm: The custom authentication realm to authenticate with. Set this as required by your custom authentication provider.
If you select KERBEROS, enter the Kerberos Ticket.
If you select NONE, enter the Encrypted Connection details as described below.
Username: The name of the Neo4j database user connecting to the Neo4j database. Required when
neo4j.authentication.typeis set toBASIC.Password: The password for the Neo4j database user connecting to the Neo4j database. Required when
neo4j.authentication.typeis set toBASIC.Authentication Realm: The authentication realm to authenticate with. Leave this field empty to use the default realm.
Kerberos Ticket: Kerberos ticket to establish connection with. Required when
neo4j.authentication.typeis set toKERBEROS.Bearer Token: Bearer token to establish connection with. Required when
neo4j.authentication.typeis set toBEARER.Custom Authentication Scheme: Custom authentication scheme to establish connection with. Required when
neo4j.authentication.typeis set toCUSTOM.Custom Principal: Custom principal to establish connection with. Required when
neo4j.authentication.typeis set toCUSTOM.Custom Credentials: Custom credential to establish connection with. Required when
neo4j.authentication.typeis set toCUSTOM.Custom Authentication Realm: Custom authentication realm to authenticate with. Set this as required by your custom authentication provider.
Encrypted Connection: Defaults to
false. When set totrue, enter the following details.Trust Strategy: Select the trust strategy to use for TLS connections. Valid options are TRUST_ALL_CERTIFICATES, TRUST_CUSTOM_CA_SIGNED_CERTIFICATES, TRUST_SYSTEM_CA_SIGNED_CERTIFICATES. Upload the certificate file if you select TRUST_CUSTOM_CA_SIGNED_CERTIFICATES.
Hostname Verification Enabled: Enables or disables hostname verification during the TLS handshake.
Trust Strategy: Trust strategy to use for TLS connections. Valid options are
TRUST_ALL_CERTIFICATES,TRUST_CUSTOM_CA_SIGNED_CERTIFICATES,TRUST_SYSTEM_CA_SIGNED_CERTIFICATES. Required whenneo4j.security.encryptedis set totrue.Certificate Files: Upload the certificate files that contain X509 certificates of CAs to trust. Required when
neo4j.security.trust-strategyis set toTRUST_CUSTOM_CA_SIGNED_CERTIFICATES.Hostname Verification Enabled: Specify whether hostname verification is enabled during the TLS handshake.
Click Continue.
Note
The connector requires that you assign exactly one strategy per topic. This strategy must be one of the following: Cypher, Pattern, CDC, or CUD.
Input Kafka record value format: Select the input Kafka record value format (data coming from the Kafka topic). A valid schema must be available in Schema Registry to use a schema-based message format (for example, AVRO, JSON_SR (JSON Schema), or PROTOBUF). Defaults to AVRO.
For more information, see Schema Registry Enabled Environments.
Common Sink Settings
Batch Size: The maximum number of messages the connector processes per transaction per topic. Defaults to
1000.Batch Timeout: The maximum amount of time the connector allows a batch to be processed. Valid units are
ms,s,m,h, andd. Defaults tos.
Cypher Strategy
Cypher Statement for Topic: The Cypher statement the connector runs for the specified topic. For example:
{ "my-topic1": "MERGE (n:Person {name: __value.name})", "my-topic2": "MATCH (n:Person {name: __value.name}) SET n.age = __value.age" }Bind Timestamp As: Specifies the name under which the message timestamp is bound in Cypher statements. Set this to an empty string to disable binding.
Bind Header As: Specifies the name under which the message header is bound in Cypher statements (bound as a map of header names to values). Set to an empty string to disable binding.
Bind Key As: The name under which the message key is bound in Cypher statements. Set to an empty string to disable binding.
Bind Value As: The name under which the message value is bound in Cypher statements. Set to an empty string to disable binding.
Bind Value As Event: Specify whether the message value will be bound as event in Cypher statements for backward compatibility.
Pattern Strategy
Node/Relationship Pattern for Topic: The node or relationship pattern the connector applies to messages received from the specified topic. For example,
{"user1": "(:User{!userId})", "user2": "(:User{!userId})-[:KNOWS]→(:User{!otherUserId})"}Merge Node Properties: Specifies whether to merge incoming properties with existing node properties.
Merge Relationship Properties: Specifies whether to merge incoming properties with existing relationship properties.
Pattern Bind Timestamp As: The name under which the message timestamp is bound in patterns. Set to an empty string to disable binding.
Pattern Bind Header As: The name under which the message header is bound in patterns (bound as a map of header names to values). Set to an empty string to disable binding.
Pattern Bind Key As: The name under which the message key is bound in patterns. Set to an empty string to disable binding.
Pattern Bind Value As: The name under which the message value is bound in patterns. Set to an empty string to disable binding.
CDC Strategy
CDC Event Topics: The topic(s) that contain CDC events generated by a Source instance using the CDC source strategy.
CDC Source ID Topics: The topic(s) that contain CDC events generated by a Source instance using the CDC source strategy.
CDC Source ID Label Name: The label name attached to the nodes managed by the
CDC Source Idstrategy.CDC Source ID Property Name: The ID property name attached to the nodes managed by the
CDC Source Idstrategy.
CUD Strategy
CUD Event Topics: The topic(s) that contain CUD (Create, Update, Delete) events.
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?.
Input Kafka record key format: Select the input Kafka record key format. Options are AVRO, JSON, STRING. A valid schema must be available in Schema Registry to use a schema-based message format like AVRO.
Additional Configs
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.
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.
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.
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.
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.
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.
Value Converter Connect Meta Data: Allow the Connect converter to add its metadata to the output schema. Applicable for 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: How to construct the subject name for key schema registration.
Auto-restart policy
Enable Connector Auto-restart: Control 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 tofalseto disable auto-restart for failed connectors. In such cases, you would need to manually restart the connector.
Consumer configuration
Max poll interval(ms): Set the maximum delay between subsequent consume requests to Kafka. Use this property to improve connector performance in cases when the connector cannot send records to the sink system. The default is 300,000 milliseconds (5 minutes).
Max poll records: Set the maximum number of records to consume from Kafka in a single request. Use this property to improve connector performance in cases when the connector cannot send records to the sink system. The default is 500 records.
Transforms
Single Message Transforms: To add a new SMT, see Add transforms. For more information about unsupported SMTs, see Unsupported transformations.
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.
For all property values and definitions, see Configuration Properties.
Click Continue.
Based on the number of topic partitions you select, you will be provided with a recommended number of tasks.
To change the number of recommended tasks, enter the number of tasks for the connector to use in the Tasks field. More tasks may improve performance.
Click Continue.
Verify the connection details.
Click Launch.
The status for the connector should go from Provisioning to Running.
Step 5: Check for records
Verify that records are being produced in your Neo4j database.
For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.
Tip
When you launch a connector, a Dead Letter Queue topic is automatically created. See View Connector Dead Letter Queue Errors in Confluent Cloud for details.
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 completed.
Step 1: List the available connectors
Enter the following command to list available connectors:
confluent connect plugin list
Step 2: List the connector configuration properties
Enter the following command to show the connector configuration properties:
confluent connect plugin describe <connector-plugin-name>
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.
Note
The connector requires that you assign exactly one strategy per topic. This strategy must be one of the following: Cypher, Pattern, CDC, or CUD.
{
"connector.class": "Neo4jSink",
"name": "Neo4jSinkConnector_1",
"schema.context.name": "default",
"kafka.auth.mode": "SERVICE_ACCOUNT",
"kafka.service.account.id": "sa-devczmg337z",
"neo4j.uri": "neo4j+s://xxxx.databases.neo4j.io",
"neo4j.authentication.type": "BASIC",
"neo4j.authentication.basic.username": "neo4j",
"neo4j.authentication.basic.password": "xxxxxxxxx",
"neo4j.security.encrypted": "false",
"neo4j.batch-size": "1000",
"neo4j.batch-timeout": "0s",
"neo4j.cypher.topic.map": "{\"neo4j-dummy-topic\": \"MERGE (n:Record {uuid: coalesce(event.f1, apoc.create.uuid())}) SET n += event\"}",
"neo4j.cypher.bind-timestamp-as": "__timestamp",
"neo4j.cypher.bind-header-as": "__header",
"neo4j.cypher.bind-key-as": "__key",
"neo4j.cypher.bind-value-as": "__value",
"neo4j.cypher.bind-value-as-event": "true",
"neo4j.pattern.topic.map": "{}",
"neo4j.pattern.merge-node-properties": "false",
"neo4j.pattern.merge-relationship-properties": "false",
"neo4j.pattern.bind-timestamp-as": "__timestamp",
"neo4j.pattern.bind-header-as": "__header",
"neo4j.pattern.bind-key-as": "__key",
"neo4j.pattern.bind-value-as": "__value",
"neo4j.cdc.source-id.label-name": "SourceEvent",
"neo4j.cdc.source-id.property-name": "sourceId",
"value.converter.replace.null.with.default": "true",
"value.converter.reference.subject.name.strategy": "DefaultReferenceSubjectNameStrategy",
"value.converter.schemas.enable": "false",
"errors.tolerance": "all",
"value.converter.ignore.default.for.nullables": "false",
"value.converter.decimal.format": "BASE64",
"value.converter.value.subject.name.strategy": "TopicNameStrategy",
"key.converter.key.subject.name.strategy": "TopicNameStrategy",
"max.poll.interval.ms": "300000",
"max.poll.records": "500",
"input.data.format": "JSON",
"input.key.format": "JSON",
"tasks.max": "1",
"topics": "neo4j-dummy-topic",
"auto.restart.on.user.error": "true"
}
Note the following property definitions:
"connector.class": Identifies the connector plugin name."input.data.format": Sets the input Kafka record value format (data coming from the Kafka topic). Valid entries are AVRO, JSON_SR, PROTOBUF, or JSON. You must have Confluent Cloud Schema Registry configured if using a schema-based message format (for example, Avro, JSON_SR (JSON Schema), or Protobuf)."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_ACCOUNTorKAFKA_API_KEY(the default). To use an API key and secret, specify the configuration propertieskafka.api.keyandkafka.api.secret, as shown in the example configuration (above). To use a service account, specify the Resource ID in the propertykafka.service.account.id=<service-account-resource-ID>. To list the available service account resource IDs, use the following command:confluent iam service-account list
For example:
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
"neo4j.uri": A URI with the formneo4j+s://c8560e2d.databases.neo4j.io."neo4j.database": The name of your Neo4j database."neo4j.authentication.type": The Neo4j authentication type to authenticate with the database. Valid options areNONE,BASIC,KERBEROS,BEARER, andCUSTOM. Defaults toBASIC."neo4j.batch-size": The maximum number of messages the connector processes per transaction per topic. Defaults to1000."neo4j.batch-timeout": The maximum amount of time the connector allows a batch to be processed. Valid units arems,s,m,h, andd. Defaults tos."tasks": The number of tasks to use with the connector. More tasks may improve performance.
Single Message Transforms: See the Single Message Transforms (SMT) documentation for details about adding SMTs using the Confluent CLI.
For all configuration property values and descriptions, see Configuration Properties.
Step 4: Load the properties file and create the connector
Enter the following command to load the configuration and start the connector:
confluent connect cluster create --config-file <file-name>.json
For example:
confluent connect cluster create --config-file Neo4j-sink-config.json
Example output:
Created connector Neo4jSinkConnector_0 lcc-do6vzd
Step 4: Check the connector status.
Enter the following command to check the connector status:
confluent connect cluster list
Example output:
ID | Name | Status | Type | Trace
+------------+-------------------------------+---------+------+-------+
lcc-do6vzd | Neo4jSinkConnector_0 | RUNNING | sink | |
Step 5: Check for records
Verify that records are populating the endpoint.
For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.
Tip
When you launch a connector, a Dead Letter Queue topic is automatically created. See View Connector Dead Letter Queue Errors in Confluent Cloud for details.
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.
How should we connect to your data?
nameSets a name for your connector.
Type: string
Valid Values: A string at most 64 characters long
Importance: high
Schema Config
schema.context.nameAdd 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
Kafka Cluster credentials
kafka.auth.modeKafka Authentication mode. It can be one of KAFKA_API_KEY or SERVICE_ACCOUNT. It defaults to KAFKA_API_KEY mode.
Type: string
Default: KAFKA_API_KEY
Valid Values: KAFKA_API_KEY, SERVICE_ACCOUNT
Importance: high
kafka.api.keyKafka API Key. Required when kafka.auth.mode==KAFKA_API_KEY.
Type: password
Importance: high
kafka.service.account.idThe Service Account that will be used to generate the API keys to communicate with Kafka Cluster.
Type: string
Importance: high
kafka.api.secretSecret associated with Kafka API key. Required when kafka.auth.mode==KAFKA_API_KEY.
Type: password
Importance: high
Connection
neo4j.uriThe Neo4j endpoint URL. For example,
neo4j+s://xxxx.databases.neo4j.io. You can specify multiple URIs separated by a comma (,).Type: string
Default: “”
Importance: high
neo4j.databaseThe name of your Neo4j database.
Type: string
Default: “”
Importance: high
neo4j.authentication.typeAuthentication type to use to authenticate with the database. Valid values are
NONE,BASIC,KERBEROS,BEARER,CUSTOM.Type: string
Default: BASIC
Valid Values: BASIC, BEARER, CUSTOM, KERBEROS, NONE
Importance: high
neo4j.authentication.basic.usernameThe name of the Neo4j database user connecting to the Neo4j database. Required when
neo4j.authentication.typeis set toBASIC.Type: string
Default: “”
Importance: high
neo4j.authentication.basic.passwordThe password for the Neo4j database user connecting to the Neo4j database. Required when
neo4j.authentication.typeis set toBASIC.Type: password
Default: [hidden]
Importance: high
neo4j.authentication.basic.realmThe authentication realm to authenticate with. Leave this field empty to use the default realm.
Type: string
Default: “”
Importance: low
neo4j.authentication.kerberos.ticketKerberos ticket to establish connection with. Required when
neo4j.authentication.typeis set toKERBEROS.Type: password
Default: [hidden]
Importance: high
neo4j.authentication.bearer.tokenBearer token to establish connection with. Required when
neo4j.authentication.typeis set toBEARER.Type: password
Default: [hidden]
Importance: high
neo4j.authentication.custom.schemeCustom authentication scheme to establish connection with. Required when
neo4j.authentication.typeis set toCUSTOM.Type: string
Default: “”
Importance: high
neo4j.authentication.custom.principalCustom principal to establish connection with. Required when
neo4j.authentication.typeis set toCUSTOM.Type: string
Default: “”
Importance: high
neo4j.authentication.custom.credentialsCustom credential to establish connection with. Required when
neo4j.authentication.typeis set toCUSTOM.Type: password
Default: [hidden]
Importance: high
neo4j.authentication.custom.realmCustom authentication realm to authenticate with. Set this as required by your custom authentication provider.
Type: string
Default: “”
Importance: high
neo4j.security.encryptedSpecify whether connection encryption is enabled. Only applicable when bolt or neo4j schemes are used inside the
neo4j.uri.Type: boolean
Default: false
Importance: low
neo4j.security.trust-strategyTrust strategy to use for TLS connections. Valid options are
TRUST_ALL_CERTIFICATES,TRUST_CUSTOM_CA_SIGNED_CERTIFICATES,TRUST_SYSTEM_CA_SIGNED_CERTIFICATES. Required whenneo4j.security.encryptedis set totrue.Type: string
Default: TRUST_SYSTEM_CA_SIGNED_CERTIFICATES
Valid Values: TRUST_ALL_CERTIFICATES, TRUST_CUSTOM_CA_SIGNED_CERTIFICATES, TRUST_SYSTEM_CA_SIGNED_CERTIFICATES
Importance: low
neo4j.security.cert-filesUpload the certificate files that contain X509 certificates of CAs to trust. Required when
neo4j.security.trust-strategyis set toTRUST_CUSTOM_CA_SIGNED_CERTIFICATES.Type: password
Importance: low
neo4j.security.hostname-verification-enabledSpecify whether hostname verification is enabled during the TLS handshake.
Type: boolean
Default: true
Importance: low
Common Sink Settings
neo4j.batch-sizeThe maximum number of messages the connector processes per transaction per topic.
Type: int
Default: 1000
Valid Values: [1000,…,100000]
Importance: medium
neo4j.batch-timeoutThe maximum amount of time the connector allows a batch to be processed. Valid units are
ms,s,m,h, andd. Defaults tos.Type: string
Default: 0s
Valid Values: Must match the regex
^[0-9]\d*(ms|s|m|h|d)$Importance: medium
Cypher Strategy
neo4j.cypher.topic.mapCypher statement to run for the specified topic. For example, {“my-topic1”: “MERGE (n:Person {name: __value.name})”, “my-topic2”: “MATCH (n:Person {name: __value.name}) SET n.age = __value.age”}
Type: string
Default: {}
Importance: medium
neo4j.cypher.bind-timestamp-asSpecify the name under which the message timestamp will be bound in Cypher statements. Set this to an empty string to disable binding.
Type: string
Default: __timestamp
Importance: medium
neo4j.cypher.bind-header-asSpecify the name under which the message header will be bound in Cypher statements (bound as a map of header names to values). Set to an empty string to disable binding.
Type: string
Default: __header
Importance: medium
neo4j.cypher.bind-key-asThe name under which the message key will be bound in Cypher statements. Set to an empty string to disable binding.
Type: string
Default: __key
Importance: medium
neo4j.cypher.bind-value-asThe name under which the message value will be bound in Cypher statements. Set to an empty string to disable binding.
Type: string
Default: __value
Importance: medium
neo4j.cypher.bind-value-as-eventSpecify whether the message value will be bound as event in Cypher statements for backward compatibility.
Type: boolean
Default: true
Importance: medium
Pattern Strategy
neo4j.pattern.topic.mapThe node or relationship pattern the connector applies to messages received from the specified topic. For example, {“user1”: “(:User{!userId})”, “user2”: “(:User{!userId})-[:KNOWS]→(:User{!otherUserId})”}
Type: string
Default: {}
Importance: medium
neo4j.pattern.merge-node-propertiesSpecify whether to merge incoming properties with existing properties of nodes.
Type: boolean
Default: false
Importance: medium
neo4j.pattern.merge-relationship-propertiesSpecify whether to merge incoming properties with existing properties of relationships.
Type: boolean
Default: false
Importance: medium
neo4j.pattern.bind-timestamp-asThe name under which the message timestamp will be bound in patterns. Set to an empty string to disable binding.
Type: string
Default: __timestamp
Importance: medium
neo4j.pattern.bind-header-asThe name under which the message header will be bound in patterns (bound as a map of header names to values). Set to an empty string to disable binding.
Type: string
Default: __header
Importance: medium
neo4j.pattern.bind-key-asThe name under which the message key will be bound in patterns. Set to an empty string to disable binding.
Type: string
Default: __key
Importance: medium
neo4j.pattern.bind-value-asThe name under which the message value will be bound in patterns. Set to an empty string to disable binding.
Type: string
Default: __value
Importance: medium
CDC Strategy
neo4j.cdc.schema.topicsThe topic(s) that contain CDC events generated by a Source instance of this connector using CDC source strategy.
Type: string
Default: “”
Importance: medium
neo4j.cdc.source-id.topicsThe topic(s) that contain CDC events generated by a Source instance of this connector using CDC source strategy.
Type: string
Default: “”
Importance: medium
neo4j.cdc.source-id.label-nameThe label name attached to the nodes managed by the
CDC Source Idstrategy.Type: string
Default: SourceEvent
Importance: medium
neo4j.cdc.source-id.property-nameThe ID property name attached to the nodes managed by the
CDC Source Idstrategy.Type: string
Default: sourceId
Importance: medium
CUD Strategy
neo4j.cud.topicsThe topic(s) that contain CUD (Create, Update, Delete) events.
Type: string
Default: “”
Importance: medium
Additional Configs
consumer.override.auto.offset.resetDefines the behavior of the consumer when there is no committed position (which occurs when the group is first initialized) or when an offset is out of range. You can choose either to reset the position to the “earliest” offset (the default) or the “latest” offset. You can also select “none” if you would rather set the initial offset yourself and you are willing to handle out of range errors manually. More details: https://docs.confluent.io/platform/current/installation/configuration/consumer-configs.html#auto-offset-reset
Type: string
Importance: low
consumer.override.isolation.levelControls how to read messages written transactionally. If set to read_committed, consumer.poll() will only return transactional messages which have been committed. If set to read_uncommitted (the default), consumer.poll() will return all messages, even transactional messages which have been aborted. Non-transactional messages will be returned unconditionally in either mode. More details: https://docs.confluent.io/platform/current/installation/configuration/consumer-configs.html#isolation-level
Type: string
Importance: low
header.converterThe converter class for the headers. This is used to serialize and deserialize the headers of the messages.
Type: string
Importance: low
value.converter.allow.optional.map.keysAllow optional string map key when converting from Connect Schema to Avro Schema. Applicable for Avro Converters.
Type: boolean
Importance: low
value.converter.auto.register.schemasSpecify if the Serializer should attempt to register the Schema.
Type: boolean
Importance: low
value.converter.connect.meta.dataAllow the Connect converter to add its metadata to the output schema. Applicable for Avro Converters.
Type: boolean
Importance: low
value.converter.enhanced.avro.schema.supportEnable enhanced schema support to preserve package information and Enums. Applicable for Avro Converters.
Type: boolean
Importance: low
value.converter.enhanced.protobuf.schema.supportEnable enhanced schema support to preserve package information. Applicable for Protobuf Converters.
Type: boolean
Importance: low
value.converter.flatten.unionsWhether to flatten unions (oneofs). Applicable for Protobuf Converters.
Type: boolean
Importance: low
value.converter.generate.index.for.unionsWhether to generate an index suffix for unions. Applicable for Protobuf Converters.
Type: boolean
Importance: low
value.converter.generate.struct.for.nullsWhether to generate a struct variable for null values. Applicable for Protobuf Converters.
Type: boolean
Importance: low
value.converter.int.for.enumsWhether to represent enums as integers. Applicable for Protobuf Converters.
Type: boolean
Importance: low
value.converter.latest.compatibility.strictVerify latest subject version is backward compatible when use.latest.version is true.
Type: boolean
Importance: low
value.converter.object.additional.propertiesWhether to allow additional properties for object schemas. Applicable for JSON_SR Converters.
Type: boolean
Importance: low
value.converter.optional.for.nullablesWhether nullable fields should be specified with an optional label. Applicable for Protobuf Converters.
Type: boolean
Importance: low
value.converter.optional.for.proto2Whether proto2 optionals are supported. Applicable for Protobuf Converters.
Type: boolean
Importance: low
value.converter.scrub.invalid.namesWhether 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.versionUse latest version of schema in subject for serialization when auto.register.schemas is false.
Type: boolean
Importance: low
value.converter.use.optional.for.nonrequiredWhether to set non-required properties to be optional. Applicable for JSON_SR Converters.
Type: boolean
Importance: low
value.converter.wrapper.for.nullablesWhether nullable fields should use primitive wrapper messages. Applicable for Protobuf Converters.
Type: boolean
Importance: low
value.converter.wrapper.for.raw.primitivesWhether a wrapper message should be interpreted as a raw primitive at root level. Applicable for Protobuf Converters.
Type: boolean
Importance: low
errors.toleranceUse 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: all
Importance: low
key.converter.key.subject.name.strategyHow to construct the subject name for key schema registration.
Type: string
Default: TopicNameStrategy
Importance: low
key.converter.replace.null.with.defaultWhether 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.enableInclude 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.formatSpecify 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.unionsWhether to flatten singleton unions. Applicable for Avro and JSON_SR Converters.
Type: boolean
Default: false
Importance: low
value.converter.ignore.default.for.nullablesWhen 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.strategySet 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.defaultWhether 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.enableInclude 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.subject.name.strategyDetermines how to construct the subject name under which the value schema is registered with Schema Registry.
Type: string
Default: TopicNameStrategy
Importance: low
Consumer configuration
max.poll.interval.msThe maximum delay between subsequent consume requests to Kafka. This configuration property may be used to improve the performance of the connector, if the connector cannot send records to the sink system. Defaults to 300000 milliseconds (5 minutes).
Type: long
Default: 300000 (5 minutes)
Valid Values: [60000,…,1800000] for non-dedicated clusters and [60000,…] for dedicated clusters
Importance: low
max.poll.recordsThe maximum number of records to consume from Kafka in a single request. This configuration property may be used to improve the performance of the connector, if the connector cannot send records to the sink system. Defaults to 500 records.
Type: long
Default: 500
Valid Values: [1,…,500] for non-dedicated clusters and [1,…] for dedicated clusters
Importance: low
Input messages
input.data.formatSets the input Kafka record value format. Valid entries are AVRO, JSON_SR, PROTOBUF, JSON or BYTES. 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: JSON
Importance: high
input.key.formatSets the input Kafka record key format. Valid entries are AVRO, BYTES, JSON, JSON_SR, PROTOBUF, or STRING. 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: JSON
Valid Values: AVRO, BYTES, JSON, JSON_SR, PROTOBUF, STRING
Importance: high
Number of tasks for this connector
tasks.maxMaximum number of tasks for the connector.
Type: int
Valid Values: [1,…]
Importance: high
Which topics do you want to get data from?
topics.regexA regular expression that matches the names of the topics to consume from. This is useful when you want to consume from multiple topics that match a certain pattern without having to list them all individually.
Type: string
Importance: low
topicsIdentifies the topic name or a comma-separated list of topic names.
Type: list
Importance: high
errors.deadletterqueue.topic.nameThe name of the topic to be used as the dead letter queue (DLQ) for messages that result in an error when processed by this sink connector, or its transformations or converters. Defaults to ‘dlq-${connector}’ if not set. The DLQ topic will be created automatically if it does not exist. You can provide
${connector}in the value to use it as a placeholder for the logical cluster ID.Type: string
Default: dlq-${connector}
Importance: low
Auto-restart policy
auto.restart.on.user.errorEnable connector to automatically restart on user-actionable errors.
Type: boolean
Default: true
Importance: medium
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. This example also shows how to use Confluent CLI to manage your resources in Confluent Cloud.
