How to do Data Modeling for Distributed Postgres in Azure Cosmos DB
summary
Explains how Azure Cosmos DB for Postgres uses the open-source Citus extension to turn tables into shards across coordinator and worker nodes via create_distributed_table_concurrently, then gives five concrete tips: pick a high-cardinality shard key that matches your app’s natural dimension, co-locate large tables and make small ones replicated, use JSONB with GIN indexing for semi-structured payloads, add time-based partitions and automatic data partitioning and archival to drop or compress old data, and always scope queries to the shard key.
AI-written summary · about
chapters (5)
- 0:00Introduction
- 0:16Azure Cosmos DB for Postgres
- 4:50Tip 1 Natural Dimension
- 6:32Tip 2 Colocation
- 12:17Summary
related talks
59mLearn Live: Model data for Azure Cosmos DB for PostgreSQL
52mBuilding Distributed OLTP with Azure Cosmos DB for PostgreSQL
44mMulti-tenant SaaS apps made simple on Azure Cosmos DB for PostgreSQL
27mMulti-tenant Saas apps made simple on Azure Cosmos DB for PostgreSQL
31mKEYNOTE: The Distributed PostgreSQL Problem & How Citus Solves it
24mCitus from the Customer eyes
32mAuto scaling Azure Cosmos DB for PostgreSQL with Citus, Grafana & Azure Serverless
28mEfficiently distributing Postgres with Citus – How to choose the right shard key?
