PostgreSQL horizontal scaling — 3 approaches in 2026

PostgreSQL horizontal scaling involves distributing workload across multiple nodes to address limitations in read throughput, analytical query volume, or write fan-out, which a single instance may struggle to handle. The main strategies for achieving this include read replicas for distributing read traffic, analytical offload to ClickHouse® via Tinybird for handling heavy analytical queries, and Citus for sharding data across multiple nodes to manage write throughput. Each option has specific use cases: read replicas are suitable for increasing read throughput, analytical offload is ideal when analytical queries slow down PostgreSQL, and Citus is effective when write throughput needs distribution. These methods introduce different levels of operational complexity and infrastructure requirements, with Citus being the most complex. Choosing the right approach requires understanding the specific workload saturation, whether it's read, write, or analytical query load. Analytical offload to ClickHouse® is highlighted as a particularly efficient solution, freeing PostgreSQL from analytical burdens and allowing it to focus on OLTP workloads.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.