Latest Posts

Stay up to date with the latest news and updates from ParadeDB.

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Engineering

How We Optimized Top K in Postgres

How ParadeDB uses principles from search engines to optimize Postgres' Top K performance.

By Ming Ying
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Engineering

Retrieve and Rerank: Personalized Search Without Leaving Postgres

Build a production-grade personalized search engine entirely within Postgres using BM25 retrieval and vector-based reranking, no external infrastructure required.

By Ankit Mittal
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Engineering

Postgres as a Search Engine: The Write Performance Problem

How ParadeDB achieved 10x improved write throughput through searchable buffers, background merging, and handling Postgres HOT chains.

By Ming Ying, James Blackwood-Sewell
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Engineering

Teaching Postgres to Facet Like Elasticsearch

Introducing faceted search in ParadeDB - bringing the power of search engine faceting to PostgreSQL with single-query aggregations.

By James Blackwood-Sewell
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Engineering

Deep Dive into ParadeDB's v2 API: The Future of SQL Search

Explore ParadeDB's v2 API that eliminates schema duplication, simplifies tokenization, and provides transparent search operators for intuitive SQL-based full-text search.

By James Blackwood-Sewell
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Announcements

ParadeDB 0.20.0: Simpler and Faster

Introducing search aggregation, V2 API as default, and performance improvements that eliminate the complexity between search and analytics in a single Postgres-native system.

By Philippe Noël
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Engineering

Hybrid Search in PostgreSQL: The Missing Manual

Build production-ready hybrid search that combines BM25 lexical matching with vector similarity search, all inside PostgreSQL

By James Blackwood-Sewell
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Engineering

From Text to Token: How Tokenization Pipelines Work

Understanding how search engines transform text into tokens through character filtering, tokenization, stemming, and stopword removal.

By James Blackwood-Sewell
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Engineering

The ACID Test: Why We Think Search Needs Transactions

A developer's look at how Elasticsearch and Postgres stack up against the ACID test

By James Blackwood-Sewell
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Engineering

Elasticsearch Was Never a Database

Elasticsearch is a search engine, not a database. Here's why it falls short as a system of record.

By James Blackwood-Sewell
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Engineering

Syncing with Postgres: Logical Replication vs. ETL

Comparing ETL pipelines with PostgreSQL logical replication for data synchronization.

By Philippe Noël
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Announcements

Announcing Our $12M Series A

Announcing our Series A funding round to accelerate ParadeDB development.

By Ming Ying
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Engineering

We Made Postgres Writes Faster, but it Broke Replication

Exploring LSM tree implementation in PostgreSQL for better write performance.

By Stu Hood, Ming Ying, Mathew Pregasen, Olive Ratliff
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Engineering

A New Postgres Block Storage Layout for Full Text Search

How we implemented a new block storage layout in Postgres for full text search performance.

By Ming Ying
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Engineering

Similarity Search with SPLADE Inside Postgres

Introducing sparse vector support in ParadeDB for efficient vector search.

By Ming Ying
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Announcements

We've Rebranded

Announcing our rebrand and new visual identity for ParadeDB.

By Ming Ying
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Engineering

Why We Picked AGPL

ParadeDB has been licensed under AGPL from day one. Here's our thought process and case study on why we picked AGPL.

By Philippe Noël
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Engineering

Full Text Search over Postgres: Elasticsearch vs. Alternatives

A comprehensive comparison between Elasticsearch and PostgreSQL for search workloads.

By Ming Ying
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Announcements

pg_search: Elastic-Quality Full Text Search Inside Postgres

Introducing the search capabilities of ParadeDB.

By Ming Ying
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Announcements

Introducing ParadeDB

We're excited to announce ParadeDB: a PostgreSQL database optimized for search.

By Ming Ying