PricingDocsTutorialsBlogAbout

Develop

Get Started
Store Embeddings
Generate Embeddings
Automatic Embedding Generation
Calculate Distance
Query Embeddings
Create Index
Quantization
Asynchronous Tasks
Weighted Vector Search
Troubleshooting
Single Operator
Postgres Notes
Security

Languages

Javascript
Python
Ruby
Rust

Migrate

Migrate from Postgres to Lantern Cloud
Migrate from pgvector to Lantern Cloud
Migrate from pgvector to self-hosted Lantern
Migrate from Pinecone to Lantern Cloud

Lantern HNSW

Installation

Lantern Extras

Installation
Generate Embeddings
Lantern Daemon

Lantern CLI

Installation
Generate Embeddings
Indexing Server
Daemon
Autotune Index
Product Quantization

Contributing

Dockerfile
Visual Studio Code

Build AI Applications with Postgres

Lantern is the only database you need for your AI applications.

  • Built on top of Postgres- Add AI to your existing applications by just writing another SQL query. We support Postgres 11 - 16.
  • Fast index creation that scales to billions of vectors- Create an HNSW index for your data in minutes (see our benchmarks).
  • Create embeddings without worrying about infrastructure- Simply select the model you'd like to use to embed your data, and we'll handle the rest. No need to worry about finding the right library, switching languages, or handling API call failures.
  • Index hyperparameter optimization- We'll automatically tune your index for you, so you don't have to worry about finding the right set of parameters, and changing them over time.

Getting Started

The easiest way to get started with Lantern is with Lantern Cloud. Lantern Cloud is a fully managed database offering with support for embedding generation and management. We also provide guides on self-hosting Lantern.

Sign up for Lantern Cloud

Explore Documentation

Check our development guide to learn more about how to use Lantern. We support generating vectors with a a variety of embedding models out of the box. With a single operator, you can query your vectors using a range of distance functions, and filter these results using your existing data.

Get Started

Store Embeddings

Create Index

Query Embeddings

Quickstart Tutorials

Integrate Lantern and vector search into an existing application by following one of our quickstart tutorials.

Python

Javascript

Java

Ruby

Get Help

If you need any help with using Lantern, reach out to our support team at support@lantern.dev.

PricingDocsTutorialsBlogAbout
LoginSign Up