ParadeDB is a Postgres for Search and Analytics
published on 2024/08/07
Today, Postgres users that need a search and analytics engine face two options: adopt an external service like Elasticsearch, which is powerful but painful to run, tune, and sync, or use Postgres’ native search and aggregations, which lack critical functionality and perform poorly over large datasets.
ParadeDB aims to be the best of both worlds, providing developers with the familiarity of Postgres and the performance of a dedicated search and analytical database.
ParadeDB is a good fit for:
- Developers who trust Postgres and don’t want to operate a non-Postgres database/query engine
- Full-text, similarity, or hybrid search over large volumes of operational data
- Backends that are bottlenecked by Postgres’ analytical performance over hundreds of millions or billions of rows
- Latency-sensitive analytical queries over external object stores like S3 and table formats like Delta Lake