Blog

Topics include vector search algorithms, use cases and applications, tutorials, templates, performance, and benchmarks

Benchmarking·Product

Product Quantization in Postgres

We implemented product quantization in Lantern and benchmarked it using the LAION 100M 768-dimensional vector dataset.

March 5, 2024 · 8 min read

Di Qi

Di Qi

Cofounder

Varik Matevosyan

Varik Matevosyan

Software Engineer

Benchmarking

Evaluating OpenAI's new embedding models with Lantern and Parea AI

OpenAI's newest embedding models promise huge performance increases. Using Lantern's Postgres vector database, and Parea AI's testing platform, we'll measure the new models in a real-world test.

February 29, 2024 · 6 min read

Di Qi

Di Qi

Cofounder

Learn

Vector databases explained

We give an overview of vector databases, and major concepts around them, including vector embeddings, vector indexing, and vector search.

March 29, 2024 · 12 min read

Di Qi

Di Qi

Cofounder

Company

Postgres vs ElasticSearch vs Algolia - Comparing the Best Search Solutions

Don't overcomplicate things with an external search engine like ElasticSearch or Algolia. Postgres as your search engine and database makes things simple and scalable for a few great reasons.

February 2, 2024 · 11 min read

Di Qi

Di Qi

Cofounder

Learn

Improving vector search over documents using HyDE

The HyDE technique uses LLMs to improve the quality of vector search over text. In this article, we explain how it works and walk through an example with Lantern as a vector database.

January 22, 2024 · 7 min read

Di Qi

Di Qi

Cofounder

Danyil Blyschak

Danyil Blyschak

Software Engineer

Embedding·Learn

Picking the right embedding model for your vector database

Why choosing the right embedding model for vector search makes all the difference, and how to experiment with embedding models more effectively with Lantern

January 15, 2024 · 12 min read

Di Qi

Di Qi

Cofounder

Danyil Blyschak

Danyil Blyschak

Software Engineer

Pinecone·Migration·Learn

Migrating from Pinecone to Lantern

Pinecone is a popular closed-source vector database. We built a Python library to support migrating data from Pinecone to Lantern. This article covers how we built it and how to use it.

January 6, 2024 · 6 min read

Di Qi

Di Qi

Cofounder

HNSW·Memory·Index·Quantization·Vector

Estimating memory footprint of your HNSW index

This interactive visualization will help you quickly reason about the resources necssary to host your embeddings and serve nearest neighbor queries over them

December 22, 2023 · 10 min read

Narek Galstyan

Narek Galstyan

Cofounder

Company

Full Text Search + Vector Search with Postgres

Search is a common need for many applications. Postgres supports search out of the box with regex matching and full text search. This can be augmented with vector search.

December 16, 2023 · 11 min read

Di Qi

Di Qi

Cofounder

Learn

The Hierarchial Navigable Small Worlds (HNSW) Algorithm

A two-part explanation of the Hierarchial Navigable Small Worlds (HNSW) Algorithm

November 19, 2023 · 4 min read

Di Qi

Di Qi

Cofounder

Learn

Embeddings and choosing the right model

An overview of embeddings and what to consider when choosing an embedding model

November 13, 2023 · 6 min read

Di Qi

Di Qi

Cofounder

Benchmarking

90x faster than pgvector — Lantern's HNSW Index Creation Time

Index creation time is a critical database metric. Learn more about how Lantern enables 90x faster index creation times than pgvector, and how Lantern compares to Pinecone.

October 20, 2023 · 8 min read

Varik Matevosyan

Varik Matevosyan

Software Engineer

Company

Launching Lantern — a PostgreSQL vector database for building AI applications

Today we’re launching Lantern, an open-source PostgreSQL vector database.

September 13, 2023 · 3 min read

Narek Galstyan

Narek Galstyan

Cofounder