EmbedInAI/EmbedInDB
A vector database that empowers AI with persistent memory
This project helps AI developers convert their existing relational databases (like MySQL, PostgreSQL, or SQL Server) into vector databases. It takes text or image data, transforms it into numerical embeddings, and stores these in your familiar database. The output is fast, similarity-based search results for AI applications. It's designed for developers building natural language processing, image recognition, or recommendation systems.
No commits in the last 6 months.
Use this if you are a developer building an AI application and want to leverage your existing relational database for efficient similarity search.
Not ideal if you are not a developer or if your AI application doesn't require integrating with a traditional SQL database for vector storage.
Stars
7
Forks
2
Language
Python
License
Apache-2.0
Category
Last pushed
May 28, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/vector-db/EmbedInAI/EmbedInDB"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
MariaDB/server
MariaDB server is a community developed fork of MySQL server. Started by core members of the...
AlayaDB-AI/AlayaLite
AlayaLite – A Fast, Flexible Vector Database for Everyone.
infiniflow/infinity
The AI-native database built for LLM applications, providing incredibly fast hybrid search of...
nnethercott/hannoy
Production-ready KV-backed HNSW implementation in Rust using LMDB
dingodb/dingo
A multi-modal vector database that supports upserts and vector queries using unified SQL...