Understanding the distinction between Kafka Streams and Kafka Connect helps optimize your streaming architecture for different use cases.

Kafka Streams:

• Client library for building stream processing applications directly on top of Kafka
• Ideal for real-time data processing, transformations, aggregations, and analytics
• Highly integrated with Kafka, allowing direct reading and writing from Kafka topics
• Best for applications requiring complex event processing and real-time computations

Kafka Connect:

• Framework for connecting Kafka with external systems including databases, file systems, and cloud services
• Provides pre-built connectors to integrate Kafka with various data sources and sinks
• Best suited for data integration, ETL processes, and moving data between systems
• Ideal for connecting Snowplow data streams to downstream storage and analytics platforms

Use case selection:

• Use Kafka Streams when you need real-time processing and transformation of Snowplow events
• Use Kafka Connect when you need to move Snowplow data from Kafka to external systems like data warehouses or analytics platforms

Both complement Snowplow's event pipeline by providing different capabilities for processing and integrating behavioral data.