Semafind/semadb
No fuss multi-index hybrid vector database / search engine
SemaDB helps you build powerful search capabilities for applications that need to find similar items or documents quickly. You feed it your data, which can include text descriptions, images (as vectors), locations, or other metadata, and it allows you to retrieve highly relevant results based on various criteria. This is useful for product managers, knowledge managers, or anyone building applications that require advanced, real-time information retrieval.
Use this if you need a flexible search engine that combines keyword, vector (similarity), and geo-location search to find relevant information in your dataset.
Not ideal if your application strictly requires simple keyword-only search or if you prefer managing traditional relational databases.
Stars
31
Forks
3
Language
Go
License
Apache-2.0
Category
Last pushed
Feb 02, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/vector-db/Semafind/semadb"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
databendlabs/databend
Data Agent Ready Warehouse : One for Analytics, Search, AI, Python Sandbox. — rebuilt from...
oceanbase/oceanbase
The Fastest Distributed Database for Transactional, Analytical, and AI Workloads.
matrixorigin/matrixone
MySQL-compatible HTAP database with Git for Data, vector search, and fulltext search....
ArcadeData/arcadedb
ArcadeDB Multi-Model Database, one DBMS that supports SQL, Cypher, Gremlin, HTTP/JSON, MongoDB...
datalevin/datalevin
A simple, fast and versatile Datalog database