Dynamically loaded extensions in Postgres in the browser
We made extensions dynamically loadable (via dlopen) into a wasm-compiled postgres, on top of pglite. The demo app showcases a restaurant search by name, and by nearest neighbor. demo: https://pglite.lantern.dev/ blog: https://lantern.dev/blog/pglite-lantern special thanks to pglite: https://github.com/electric-sql/pglite/
Dynamically loaded extensions in Postgres in the browser launched on July 12, 2024 with 9 votes, #1,537 of 5,184 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 2 years on.
What it does
We build on top of pglite to support loading Postgres extensions directly in the browser. We share a demo using geospatial search and vector search from Lantern, and discuss technical challenges we encountered.
At a recent AGI House hackathon in San Francisco, we set out to run our Postgres vector extension directly in the browser. This would allow our documentation examples and small demos to be fully executable within the browser using a Postgres instance compiled to Wasm and running on the client browser. We built on top of pglite , which uses a modified version of Postgres that enables running Postgres in the browser and NodeJS. We added support for dynamically loading extensions into pglite , and built an application demonstrating vector search inside the browser via dynamically loaded lantern and pgvector extensions. Head over to our demo app to interact with a fully functional Postgres…from lantern.dev
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PGlite – in-browser WASM Postgres with pgvector and live sync2024 · pglite.dev · ▲509Hey, Sam and the team from ElectricSQL here. PGlite is a WASM Postgres build packaged into a TypeScript/JavaScript client library, that enables you to run Postgres in the browser, Node.js and Bun, with no need to install any other dependencies. It's 3mb Gzipped, now has support for many Postgres extensions, including pgvector, and it has a reactive "live query" API. It's also fast, with CRUD style queries executing in under 0.3 ms, and larger, multi-row select queries occurring within a fraction of a single frame. PGlite started as an experimental project we shared on X, and the…
- LALantern – a PostgreSQL vector database for building AI applications2023 · docs.lantern.dev · ▲196
We are excited to share Lantern! Lantern is a PostgreSQL vector database extension for building AI applications. Install and use our extension here: https://github.com/lanterndata/lantern We have the most complete feature set of all the PostgreSQL vector database extensions. Our database is built on top of usearch — a state of the art implementation of HNSW, the most scalable and performant algorithm for handling vector search. There’s three key metrics we track. CREATE INDEX time, SELECT throughput, and SELECT latency. We match or outperform pgvector and pg_embedding…
Embed an SQLite database in your PostgreSQL table2024 · github.com · ▲180pglite-fusion is a PostgreSQL extension that allows you to embed SQLite databases into your PostgreSQL tables by enabling the creation of columns with the `SQLITE` type. This means every row in the table can have an embedded SQLite database. In addition to the PostgreSQL `SQLITE` type, pglite-fusion provides the `query_sqlite`` function for querying SQLite databases and the `execute_sqlite` function for updating them. Additional functions are listed in the project’s README. The pglite-fusion extension is written in Rust using the pgrx framework [1]. ---- Implementation Details The PostgreSQL…
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I open-sourced the in-memory PostgreSQL I built at work for E2E tests2024 · github.com · ▲379In-memory Postgres for unit/E2E tests. Contribute to hexclave/pgmock development by creating an account on GitHub.
Postgres extension for BM25 relevance-ranked full-text searchMar 2026 · github.com · ▲203Last summer we faced a conundrum at my company, Tiger Data, a Postgres cloud vendor whose main business is in timeseries data. We were trying to grow our business towards emerging AI-centric workloads and wanted to provide a state-of-the-art hybrid search stack in Postgres. We'd already built pgvectorscale in house with the goal of scaling semantic search beyond pgvector's main memory limitations. We just needed a scalable ranked keyword search solution too. The problem: core Postgres doesn't provide this; the leading Postgres BM25 extension, ParadeDB, is guarded behind AGPL; developing our…
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