Just use Postgres.
One Postgres for your application data, full-text search, vector retrieval, and aggregations.
When queries get too slow, developers usually reach for systems like Elasticsearch. ParadeDB makes text and vector search, filters, facets, and joins fast in Postgres.
Built as a Postgres extension, ParadeDB pairs Postgres' transactional storage with a unified index combining inverted, vector, and columnar data structures. Keep your application data in one place and query it with standard SQL, with ACID transactions and the Postgres tools you already use. No Elasticsearch. Zero ETL.
Explore our documentation to learn how ParadeDB works and what you can build with it. When you're ready, get started locally with Docker or build on ParadeDB Cloud.
Companies use ParadeDB to replace Elasticsearch, OpenSearch, and custom search stacks while keeping Postgres as their system of record. Explore customer stories to learn more.
We welcome contributions of all kinds — code, docs, bug reports, and feature discussions. Start by visiting paradedb/paradedb on GitHub. If you're planning a larger contribution, we recommend opening a discussion first and joining our Community Slack.
Join the ParadeDB community to ask questions, share ideas, and help shape the roadmap.
- Slack — Chat with the team and community
- GitHub Discussions — Ask questions and share ideas
- Blog — Engineering deep-dives and announcements
- X / Twitter — Follow for updates
Want to work on Postgres internals, search engines, and distributed systems? Reach out at careers@paradedb.com with your resume or GitHub profile.
For sales, partnerships, sponsorships, or media inquiries, email us at hello@paradedb.com.
