Date: 2025-10-01
Time: 11:00–11:50
Room: Room 4
Level: Beginner
PostgreSQL has earned its place as a powerhouse relational database, but as application demands increase—especially in real-time analytics, high-throughput systems, and hybrid transactional/analytical workloads—traditional scaling approaches can hit cost and complexity walls. This talk introduces a practical, non-invasive strategy to scale PostgreSQL horizontally and reduce query latency using GridGain as an in-memory computing layer.
We’ll explore how GridGain integrates with PostgreSQL to act as a distributed SQL engine and caching layer, enabling low-latency access to hot data and high-performance distributed joins—without replacing your database. Attendees will learn how to offload expensive queries, perform real-time analytics across large datasets, and scale out read-heavy workloads without resorting to sharding or complex replication schemes. Through architecture diagrams, performance benchmarks, and real-world use cases, this session equips PostgreSQL users with a modern, JVM-based approach to meet growing performance demands—while keeping PostgreSQL at the core of their stack.
Target Audience
Developers, DBAs, architects, and platform engineers working with PostgreSQL who are exploring strategies to scale read-intensive workloads, enable real-time analytics, or integrate in-memory processing into their systems.