Common Use Cases

Summary

Common Use Cases

We'll cover four major use cases: Change Data Capture, Database Ingestion, Data Lake Loading, and Elasticsearch Indexing. Each of these solves a specific class of data integration problems.

Change Data Capture (CDC)

Change Data Capture is one of the most powerful use cases for Kafka Connect. CDC captures every insert, update, and delete operation from a database and streams those changes to Kafka in real-time.

CDC Benefits

With CDC, you can build event-driven architectures where downstream systems react immediately to database changes. Instead of polling the database or using batch ETL jobs, you get a real-time stream of change events. This is perfect for keeping multiple systems synchronized, building materialized views, or feeding real-time analytics.

Debezium is the most popular CDC connector for Kafka Connect, supporting MySQL, PostgreSQL, MongoDB, SQL Server, Oracle, and more. It reads the database's transaction log to capture every change without adding load to the database.

Database Ingestion

Another common pattern is periodic database ingestion, where you regularly pull data from database tables into Kafka topics. This is useful for batch-oriented workloads or when you don't need real-time changes.

Database Ingestion Use Cases

The JDBC Source Connector can query database tables on a schedule, pulling new or updated rows based on a timestamp column or auto-incrementing ID. This pattern is great for migrating data between databases, feeding data into analytics platforms, or creating read replicas.

You can combine this with stream processing to transform, enrich, or aggregate the data before writing it to a target database using the JDBC Sink Connector. This creates a complete ETL pipeline without writing any custom code.

Data Lake Loading

Loading data into cloud data lakes is another extremely common use case. You stream events from various sources into Kafka, then use sink connectors to write that data to object storage in formats optimized for analytics.

Data Lake Benefits

The S3 Sink Connector reads from Kafka topics and writes files to S3 in batches. It can partition data by time, format data as Parquet or Avro for efficient querying, and handle schema evolution automatically.

This pattern is perfect for building data lakes where you want to retain all your event data for historical analysis. Tools like AWS Athena, Presto, or Spark can then query the data directly from S3. The same pattern works with Azure Blob Storage, Google Cloud Storage, or HDFS.

Elasticsearch Indexing

The final common pattern is indexing data into Elasticsearch for full-text search and real-time analytics. This enables powerful search capabilities across your Kafka data.

Elasticsearch Use Cases

The Elasticsearch Sink Connector consumes records from Kafka and indexes them in Elasticsearch. This is incredibly useful for log aggregation, building search features on top of your data, or creating real-time dashboards in Kibana.

For example, you could index your product catalog from a database using CDC, making it searchable with Elasticsearch's powerful query language. Or you could index application logs for troubleshooting and monitoring. The connector handles mapping Kafka records to Elasticsearch documents automatically.

Other Common Use Cases

Beyond these four major patterns, Kafka Connect is used for many other scenarios:

Message Queue Integration: Connecting legacy systems that use JMS, AMQP, or other message protocols to Kafka.

Cloud Service Integration: Syncing data with SaaS platforms like Salesforce, ServiceNow, or Google Sheets.

Stream Replication: Replicating data between Kafka clusters across data centers or cloud regions.

Cache Synchronization: Keeping Redis or Memcached caches up-to-date with database changes.

Time-Series Data: Storing IoT sensor data in InfluxDB or TimescaleDB.

These use cases demonstrate the versatility of Kafka Connect. Whether you're building real-time data pipelines, migrating data between systems, or creating analytics platforms, Kafka Connect provides battle-tested connectors that handle the complexity for you.