edwinkys/oasysdb
In-memory vector store with efficient read and write performance for semantic caching and retrieval system. Redis for Semantic Caching.
This is an in-memory database designed for developers building AI applications. It helps store and retrieve 'semantic information' or vector embeddings very quickly. It's particularly useful for handling large volumes of AI-generated data efficiently, acting like a fast cache for AI systems. Software engineers and AI infrastructure developers are the primary users.
379 stars. No commits in the last 6 months.
Use this if you are a software engineer building AI applications and need an extremely fast way to store and retrieve vector embeddings for semantic caching.
Not ideal if you are not a developer or if you need a persistent, fully-featured database for general-purpose data storage.
Stars
379
Forks
14
Language
Rust
License
Apache-2.0
Category
Last pushed
Nov 29, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/vector-db/edwinkys/oasysdb"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
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