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Microsoft SQL Server Source Connector for Confluent Cloud

Note

If you are installing the connector locally for Confluent Platform, see JDBC Connector (Source and Sink) for Confluent Platform.

The Kafka Connect Microsoft SQL Server Source connector for Confluent Cloud can obtain a snapshot of the existing data in a Microsoft SQL Server database and then monitor and record all subsequent row-level changes to that data. The connector supports Avro, JSON Schema, Protobuf, or JSON (schemaless) output data formats. All of the events for each table are recorded in a separate Apache Kafka® topic. The events can then be easily consumed by applications and services. Note that deleted records are not captured.

Important

If you are still on Confluent Cloud Enterprise, please contact your Confluent Account Executive for more information about using this connector.

Features

The Microsoft SQL Server source connector provides the following features:

  • Topics created automatically: The connector automatically creates Kafka topics using the naming convention: <topic.prefix><tableName>. The tables are created with the properties: topic.creation.default.partitions=1 and topic.creation.default.replication.factor=3.

  • Insert modes:

    • timestamp mode is enabled when only a timestamp column is specified when you enter database details.

    • timestamp+incrementing mode is enabled when both a timestamp column and incrementing column are specified when you enter database details.

      Important

      • A timestamp column must not be nullable.
      • A timestamp column must use datetime2 and not datetime. If the timestamp column uses datetime, the topic may receive numerous duplicates.

  • Database authentication: password authentication.

  • Data formats: The connector supports Avro, JSON Schema, Protobuf, or JSON (schemaless) output data. Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro, JSON_SR (JSON Schema), or Protobuf).

  • Select configuration properties:

    • db.timezone

    • poll.interval.ms

    • batch.max.rows

    • timestamp.delay.interval.ms

    • topic.prefix

    • schema.pattern

      Configuration properties that are not shown in the Confluent Cloud UI use the default values. See JDBC Connector Source Connector Configuration Properties for default values and property definitions.

For more information and examples to use with the Confluent Cloud API for Connect, see the Connect API for Confluent Cloud section.

For more information, see the Confluent Cloud connector limitations.

Quick Start

Use this quick start to get up and running with the Confluent Cloud Microsoft SQL Server source connector. The quick start provides the basics of selecting the connector and configuring it to obtain a snapshot of the existing data in a Microsoft SQL Server database and then monitoring and recording all subsequent row-level changes.

Prerequisites

  • Authorized access to a Confluent Cloud cluster on Amazon Web Services (AWS), Microsoft Azure (Azure), or Google Cloud Platform (GCP).

  • The Confluent Cloud CLI installed and configured for the cluster. See Install and Configure the Confluent Cloud CLI.

  • The connector automatically creates Kafka topics using the naming convention: <prefix>.<table-name>. 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, please create the topics before running this connector.

  • Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro, JSON_SR (JSON Schema), or Protobuf).

  • Public access may be required for your database. See Internet Access to Resources for details. The example below shows the AWS Management Console when setting up a Microsoft SQL Server database.

    AWS example showing public access for Microsoft SQL Server

    Public access enabled

  • Public inbound traffic access (0.0.0.0/0) may be required for the VPC where the database is located, unless the environment is configured for VPC peering. For networking considerations, see Internet Access to Resources. To use static egress IPs, see Static Egress IP Addresses. The example below shows the AWS Management Console when setting up security group rules for the VPC.

    AWS example showing security group rules

    Open inbound traffic

    Note

    See your specific cloud platform documentation for how to configure security rules for your VPC.

  • A database table timestamp column must not be nullable and must use datetime2 and not datetime.

  • Kafka cluster credentials. You can use one of the following ways to get credentials:
    • Create a Confluent Cloud API key and secret. To create a key and secret, you can use the Confluent Cloud CLI or you can autogenerate the API key and secret directly in the Confluent Cloud GUI when setting up the connector.
    • Create a Confluent Cloud service account for the connector. Make sure to review the ACL entries required in the service account documentation. Some connectors have specific ACL requirements.

Using the Confluent Cloud GUI

Step 1: Launch your Confluent Cloud cluster.

See the Quick Start for Apache Kafka using Confluent Cloud for installation instructions.

Step 2: Add a connector.

Click Connectors. If you already have connectors in your cluster, click Add connector.

Step 3: Select your connector.

Click the Microsoft SQL Server Source connector icon.

Microsoft SQL Server Source Connector Icon

Step 4: Set up the connection.

Complete the following and click Continue.

Note

  • Make sure you have all your prerequisites completed.
  • An asterisk ( * ) designates a required entry.

  1. Enter a connector name.

  2. Enter your Kafka Cluster credentials. The credentials are either the API key and secret or the service account API key and secret.

  3. Enter a topic prefix. The connector automatically creates Kafka topics using the naming convention: <prefix>.<table-name>. 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, please create the topics before running this connector.

  4. Add the connection details for the database.

    Important

    Do not include jdbc:xxxx:// in the Connection host field. The example below shows a sample host address.

    ../_images/ccloud-postgresql-source-connect-to-data.png

  5. Add the Database details for your database. Review the following notes for more information about field selections.

    • Enter a Timestamp column name to enable timesamp mode. This mode uses a timestamp (or timestamp-like) column to detect new and modified rows. This assumes the column is updated with each write, and that values are monotonically incrementing, but not necessarily unique.

    • Enter both a Timestamp column name and an Incrementing column name to enable timestamp+incrementing mode. This mode uses two columns, a timestamp column that detects new and modified rows, and a strictly incrementing column which provides a globally unique ID for updates so each row can be assigned a unique stream offset.

    • By default, the connector only detects tables with type TABLE from the source database. Use VIEW for virtual tables created from joining one or more tables. Use ALIAS for tables with a shortened or temporary name.

    • If you define a schema pattern in your database, you need to enter the Schema pattern in this field. For more information, search for schema.pattern in JDBC Connector Source Connector Configuration Properties.

      Note

      Configuration properties that are not shown in the Confluent Cloud UI use the default values. For default values and property definitions, see JDBC Connector Source Connector Configuration Properties.

  6. Add the Connection details for your connection to the database.

  7. Select an Output message format (data coming from the connector): AVRO, JSON_SR (JSON Schema), PROTOBUF, or JSON (schemaless). 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).

  8. Enter the number of tasks in use by the connector. Refer to Confluent Cloud connector limitations for additional information.

Step 5: Launch the connector.

Verify the connection details and click Launch.

Launch the connector

Step 6: Check the connector status.

The status for the connector should go from Provisioning to Running. It may take a few minutes.

Check the connector status

Step 7: Check the Kafka topic.

After the connector is running, verify that messages are populating your Kafka topic.

For more information and examples to use with the Confluent Cloud API for Connect, see the Connect API for Confluent Cloud section.

For additional information about this connector, see JDBC Connector (Source and Sink) for Confluent Platform. Note that not all Confluent Platform connector features are provided in the Confluent Cloud connector.

See also

For an example that shows fully-managed Confluent Cloud connectors in action with Confluent Cloud ksqlDB, see the Cloud ETL Demo. This example also shows how to use Confluent Cloud CLI to manage your resources in Confluent Cloud.

../_images/topology.png

Using the Confluent Cloud CLI

Complete the following steps to set up and run the connector using the Confluent Cloud CLI.

Note

Make sure you have all your prerequisites completed.

Step 1: List the available connectors.

Enter the following command to list available connectors:

ccloud connector-catalog list

Step 2: Show the required connector configuration properties.

Enter the following command to show the required connector properties:

ccloud connector-catalog describe <connector-catalog-name>

For example:

ccloud connector-catalog describe MicrosoftSqlServerSource

Example output:

Following are the required configs:
connector.class
name
kafka.api.key
kafka.api.secret
topic.prefix
connection.host
connection.port
connection.user
connection.password
db.name
table.whitelist
timestamp.column.name
output.data.format
tasks.max

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.

{
    "name" : "confluent-microsoft-sql-source",
    "connector.class": "MicrosoftSqlServerSource",
    "kafka.api.key": "<my-kafka-api-key>",
    "kafka.api.secret" : "<my-kafka-api-secret>",
    "topic.prefix" : "microsoftsql_",
    "connection.host" : "<my-database-endpoint>",
    "connection.port" : "1433",
    "connection.user" : "<database-username>",
    "connection.password": "<database-password>",
    "db.name": "ms-sql-test",
    "table.whitelist": "passengers",
    "timestamp.column.name": "created_at",
    "output.data.format": "JSON",
    "db.timezone": "UCT",
    "tasks.max" : "1"
}

Note the following property definitions:

  • "topic.prefix": Enter a topic prefix. The connector automatically creates Kafka topics using the naming convention: <prefix>.<table-name>. 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, please create the topics before running this connector.
  • "output.data.format": Sets the output message format (data coming from the connector). 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).
  • "db.timezone": Identifies the database timezone. This can be any valid database timezone. The default is UTC. For more information, see this list of database timezones.

Note

Configuration properties that are not listed use the default values. For default values and property definitions, see JDBC Connector Source Connector Configuration Properties.

Step 4: Load the properties file and create the connector.

Enter the following command to load the configuration and start the connector:

ccloud connector create --config <file-name>.json

For example:

ccloud connector create --config microsoft-sql-source.json

Example output:

Created connector confluent-microsoft-sql-source lcc-ix4dl

Step 5: Check the connector status.

Enter the following command to check the connector status:

ccloud connector list

Example output:

ID          |            Name                | Status  |  Type
+-----------+--------------------------------+---------+-------+
lcc-ix4dl   | confluent-microsoft-sql-source | RUNNING | source

Step 6: Check the Kafka topic.

After the connector is running, verify that messages are populating your Kafka topic.

For more information and examples to use with the Confluent Cloud API for Connect, see the Connect API for Confluent Cloud section.

For additional information about this connector, see JDBC Connector (Source and Sink) for Confluent Platform. Note that not all Confluent Platform connector features are provided in the Confluent Cloud connector.

Next Steps

See also

For an example that shows fully-managed Confluent Cloud connectors in action with Confluent Cloud ksqlDB, see the Cloud ETL Demo. This example also shows how to use Confluent Cloud CLI to manage your resources in Confluent Cloud.

../_images/topology.png