Caching and Beyond - Smarter Data Processing with Java
summary
Claims that replacing heavy DB usage with Java-native storage cuts complexity, infra and license costs while speeding apps; demo builds an app using Eclipse Store (GigaMap) with Lucene index and PostgreSQL, wires Debezium CDC to update cache, and runs replication via a Helm chart/SaaS. Example loads 20k–200k book rows, shows warm reads drop from ~168ms to ~10ms and reports ~12,000 RPM vs ~400 RPM vs the database, uses ~300MB RAM vs much higher for the Hibernate stack, and the replication/CDC pipeline works live.
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chapters (9)
- 0:00Introduction and speaker intro
- 1:19Meaning and purpose of caching
- 9:55Challenges and considerations in caching
- 16:18Caching patterns explained
- 24:13Demo setup and performance comparison
- 30:47Eclipse Store architecture overview
- 37:31Updating cache with Debezium
- 40:21Cache replication in cloud
- 41:46Q&A session
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