Databases 2 min read

Hands‑On Guide to Hyperscale (Citus): Building Scalable Distributed PostgreSQL Applications

This guide explains how Hyperscale (Citus) extends PostgreSQL with distributed tables, enabling developers to start on a single node and seamlessly scale to multiple nodes for high‑throughput SaaS, real‑time analytics, and time‑series workloads across many industry verticals.

Hacker Afternoon Tea
Hacker Afternoon Tea
Hacker Afternoon Tea
Hands‑On Guide to Hyperscale (Citus): Building Scalable Distributed PostgreSQL Applications

What is Hyperscale (Citus)?

Hyperscale (Citus) is a PostgreSQL extension that adds the capability of “distributed tables”. This capability lets you build highly scalable relational applications. You can start building an application on a single‑node server group just as you would with ordinary PostgreSQL. As the scalability and performance requirements grow, you can seamlessly expand to multiple nodes by transparently distributing tables.

Real‑world customer applications built on Citus include SaaS platforms, real‑time operational analytics, and high‑throughput transactional workloads. These span verticals such as sales and marketing automation, healthcare, IoT/telemetry, finance, logistics, and search.

Citus transforms Postgres into a distributed database with features such as sharding, a distributed SQL engine, reference tables, and distributed tables. By combining parallelism, keeping more data in memory, and providing higher I/O bandwidth, Citus can dramatically improve performance for multi‑tenant SaaS applications, customer‑facing real‑time analytics dashboards, and time‑series workloads.

Microsoft documentation: https://docs.microsoft.com/en-us/azure/postgresql/hyperscale/overview

Chinese manual (continuously updated): https://citus.hacker-linner.com

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real-time analyticsdistributed-databaseScalable ArchitecturePostgreSQLSaaSTime SeriesCitus
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