Hey everyone! I’m excited to share a project I’ve been working on: PardusDB.
If you’ve ever built a RAG (Retrieval-Augmented Generation) app or a local AI agent, you’ve probably realized that setting up a full-blown vector cluster like Milvus or Pinecone is often overkill for smaller, local-first projects.
I wanted something that felt like SQLite—simple, embedded, and zero-config—but built specifically for vector search and document storage. So, I built it in Rust.
🚀 What is PardusDB?
PardusDB is a lightweight, high-performance, document-oriented NoSQL database. It’s designed to handle high-dimensional embeddings with a tiny footprint.
🛠 Key Features:
Embedded & Local-First: No server overhead. It lives directly in your application.
Schema-less: Store your metadata and vectors together without rigid table structures.
Rust-Powered: Fast, memory-safe, and optimized for low-latency similarity search.
Open Source: I've made the code public for anyone to use, break, and improve!
💻 Why I built it:
Most vector databases are designed for the cloud. PardusDB is for the edge, the desktop, and the developer who wants to get a vector-enabled app running in minutes, not hours.
Check out the repo here: github.com
I’d love to hear your thoughts, answer any questions, or see how you might use this in your next AI project!