An open source, object-relational database system with over 35 years of active development that has earned it a strong reputation for reliability, feature robustness, and performance.

advanced features (6)

pgvector extension (4)

advanced indexing (3)

advanced features (6)

pgvector extension (4)

advanced indexing (3)

It has to be the best open source relational DBMS software out there with a ton of amazing features including few rarely seen in others but extremely useful ones like partial indexes, lateral joins and even support for no-sql like data structures like JSON and now even vector data.

My passion for Postgres stems from its versatility and robustness; it’s my go-to for data analytics projects, streamlining data engineering tasks through Supabase, and enhancing SQL workflows in VS Code with the SQLTools extension. Its seamless integration with Excel only solidifies its position as an indispensable tool in my data toolkit.

PostgreSQL is a very robust and performant SQL Database that exists currently. I've studied its internal architecture and I find it's very well thought through and every component of the architecture has a defined role to make it battle-tested production-grade DB.

Having worked with Oracle in the past, I’ve come to appreciate PostgreSQL for its flexibility, performance, and strong community support. It’s definitely a front-runner in modern RDBMS choices.

Postgres stands out thanks to its rock‑solid reliability and rich feature set—think advanced indexing, robust JSON support, and strong concurrency. It’s open source, highly scalable, and keeps our data queries speedy without locking us into proprietary models. Alternatives Considered: MySQL: Popular, but we preferred Postgres’s deeper JSON and indexing capabilities. MongoDB: Excellent for flexible schemas, but we needed the reliability of SQL. MariaDB: Similar to MySQL, but Postgres’s community and extension ecosystem won us over.

I prefer PostgreSQL because it's just such an incredibly robust and versatile relational database that I trust. The huge advantage, especially for AI and search stuff lately, is the pgvector extension. It lets me store and run similarity searches on vector embeddings right inside my main relational database, totally avoiding the complexity of managing a separate vector database system. It feels like having the best of both worlds in one reliable platform.

PGVector's native vector operations with PostgreSQL's ACID compliance works perfectly. We're storing millions of embeddings with sub-millisecond similarity search using cosine distance. The async connection pooling handles concurrent connections, while the vector indexing makes our query super fast. Having vector search, full-text search, and relational data in one database eliminates the complexity of managing multiple data stores.

PostgreSQL

A powerful, open source object-relational database system

A powerful, open source object-relational database system

PostgreSQL Reviews

The community submitted 74 reviews to tell us what they like about PostgreSQL, what PostgreSQL can do better, and more.

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