Apache Flink: Overkill for Simple, Stateless Stream Processing and ETL?

When discussing stream processing engines, Apache Flink often takes center stage for its advanced capabilities in stateful stream processing and real-time data analytics. However, a common question arises: is Flink too heavyweight for simple, stateless stream processing and ETL tasks? The short answer for open-source Flink is often yes. But the story evolves significantly when looking at SaaS Flink products such as Confluent Cloud’s Flink offering, with its serverless architecture, multi-tenancy, consumption-based pricing, and no-code/low-code capabilities like Flink Actions. This post explores the considerations and trade-offs to help you decide when Flink is the right tool for your data streaming needs, and when Kafka Streams or Single Message Transform (SMT) within Kafka Connect are the better choice.

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The Nature of Stateless Stream Processing

Stateless stream processing, as the name implies, processes each event independently, with no reliance on prior events or context. This simplicity lends itself…