Last value cache: the no-code way with Redpanda Data Transforms

In Pub/Sub messaging systems, last value caching (LVC) is a technique used to ensure new subscribers quickly access the most recent data, suitable for applications like stock tickers that require real-time updates without historical data. Apache Kafka supports this through compacted topics, which manage data size by removing older messages once newer versions are available, though this results in data loss unsuitable for use cases needing full historical data, such as back-testing. Traditional methods for managing LVC include dual writes, which risk data inconsistency, and streaming pipelines, which require managing external processors. Redpanda offers an innovative solution using WebAssembly-powered Data Transforms, allowing efficient, no-code, in-broker transformation that creates a consistent copy from a full to a compacted topic, addressing scalability, fault tolerance, and simplicity without external dependencies. This feature, available in Redpanda 24.1, enhances last value caching and opens possibilities for diverse applications through user-defined message transformations.

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