PGDay UK2025

Modern applications often need to handle a blend of transactional (OLTP) and analytical (OLAP) queries on the same dataset—posing a unique challenge for traditional database architectures. Citus’s sharding and partitioning features can help strike that balance. In this session, we’ll cover how to design a table layout that gracefully serves high-velocity writes and transactional queries while still enabling fast analytical aggregates. We’ll look into practical partitioning patterns, index strategies, and how to leverage co-location for analytical joins. We’ll also discuss how to monitor workload patterns so you can adjust partition sizes and distribution keys as data or query demands evolve. After this talk, you’ll have a roadmap for building adaptive data models in Postgres with Citus that can fluidly handle both OLTP and OLAP workloads.