Vector Databases

Created: Oct 18, 2022 by Pradeep Gowda . Updated: Nov 23, 2023 Tagged: databases · vectordb

A vector database indexes and stores vector embeddings for fast retrieval and similarity search, with capabilities like CRUD operations, metadata filtering, and horizontal scaling.

What is a Vector Database? from the pinecone.io team.

Common Use cases for vector search:

Semantic Search
Similarity search for images, audio, video, JSON, and other forms of unstructured data
Ranking and Recommendation Engines
Deduplication and record matching
Anomaly detection (eg: IT Threat detection)

Capabilities of a vector database:

Vector Indexes for Search and Retrieval
Single-Stage Filtering
Data Sharding
Replication
Hybrid Storage
API

Vector databases

pinecone
qdrant
chroma
FAISS
Elasticsearch

Articles

Building vector search in 200 lines of Rust
Posts · The Data Quarry – a few articles on vector databases by Prashanth Rao at The Data Quarry
VectorDB – see explanation of “Why use vector search and embeddings with large language models?” with example. Uses FAISS and mrpt under the hood.