Java's Ignored Potential: Supercharge Database Apps with Java In-Memory Process
summary
Open-source Eclipse Store and Eclipse Serializer provide byte‑level persistence of arbitrary Java object graphs (JDK 11+), an ACID on‑disk binary format, and lazy loading; an Eclipse Data Grid adds Kubernetes clustering, an index layer and a GigaMap to search billions in milliseconds while keeping native Java types and the Streams API. Benchmarks claim microsecond in‑memory access vs millisecond databases and a typical 30–50% cloud cost reduction; a customer reports $1.5M saved year one and ~$40M projected over three years.
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chapters (11)
- 0:00Welcome to JCON
- 1:04JCON and community updates
- 3:57Challenges in database performance
- 5:15Complexity of modern data architecture
- 10:28Introducing Java in-memory processing
- 11:57Eclipse store and cluster solutions
- 16:08Announcing the Eclipse data grid
- 21:04Running the stack in Oracle Cloud
- 22:13Benefits of Oracle Cloud infrastructure
- 28:11Sovereign cloud and global scale
- 29:03Real-world impact and conclusion
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