Latest Posts
Stay up to date with the latest news and updates from ParadeDB.
Making COUNTs and the Rest of Search Really Fast (Part II)
How ctid-aware segment partitioning, an inverted DocId map, and bitmap postings accelerated ParadeDB's Wikipedia COUNT queries—then a look at the rest of search, where ParadeDB delivered 10–22x TIN's throughput on filtered and time-sorted Hacker News queries.
PlanetScale Released Text Search and We Have a Lot to Say (Part I)
Two BM25 optimizations and benchmark configuration changes inspired by PlanetScale's TIN benchmarks make ParadeDB's text search faster without changing its document identifiers.
Same Query, Three Results: Benchmarking ParadeDB and Postgres FTS
Three benchmark passes over one TopK search query against ParadeDB and Postgres FTS, showing how workload variation and execution shape change the answer.
What We Think About When We Think About Benchmarking
Publishing a benchmark has two hard problems: telling a story worth reading and getting the mechanics right. Here's how we think about both.
A Conversation with Paul Masurel, Creator of Tantivy
We sat down with Paul Masurel (creator of Tantivy and co-founder of Quickwit) to talk about building a search engine in Rust, following the competitive happy-path with Lucene, open-source maintenance, and the lessons learned along the way.
How We Optimized Top K in Postgres
How ParadeDB uses principles from search engines to optimize Postgres' Top K performance.
Postgres as a Recommender Engine
Build a production-grade personalized search engine entirely within Postgres using BM25 retrieval and vector-based reranking, no external infrastructure required.
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.
Teaching Postgres to Facet Like Elasticsearch
How ParadeDB brings faceted search to PostgreSQL with single-query aggregations, from SQL syntax to planner integration and execution.
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.
Hybrid Search in PostgreSQL: The Missing Manual
Build production-ready hybrid search that combines BM25 lexical matching with vector similarity search, all inside PostgreSQL
From Text to Token: How Tokenization Pipelines Work
Understanding how search engines transform text into tokens through character filtering, tokenization, stemming, and stopword removal.
The ACID Test: Why We Think Search Needs Transactions
A developer's look at how Elasticsearch and Postgres stack up against the ACID test
Elasticsearch Was Never a Database
Elasticsearch is a search engine, not a database. Here's why it falls short as a system of record.
Syncing with Postgres: Logical Replication vs. ETL
Comparing ETL pipelines with PostgreSQL logical replication for data synchronization.
We Made Postgres Writes Faster, but it Broke Replication
Exploring LSM tree implementation in PostgreSQL for better write performance.
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.
Similarity Search with SPLADE Inside Postgres
Introducing sparse vector support in ParadeDB for efficient vector search.
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.
Full Text Search over Postgres: Elasticsearch vs. Alternatives
A comprehensive comparison between Elasticsearch and PostgreSQL for search workloads.