Building a Materialized Cache with ksqlDB

What this post added

This post introduces the concept of materialized caches and demonstrates how to build them using ksqlDB. It explains how to model change data capture as a ksqlDB stream, define a query to aggregate events within a specific geographic area and time window, and then persist this query as a materialized view (table) for efficient, low-latency querying. It also covers setting up ksqlDB with Docker Compose, interactive CLI usage, and accessing the materialized cache via ksqlDB's REST API. The post highlights the benefits of this approach for offloading read pressure from traditional databases and enabling incremental updates to query results.