Mohitkr95/qdrant-multi-node-cluster

Scalable Qdrant vector database cluster with Docker Compose, monitoring, and comprehensive documentation for high-performance similarity search applications.

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Emerging

This project helps you set up a robust and scalable Qdrant vector database for high-performance similarity search. You feed it large collections of vector data (like image embeddings or text embeddings), and it helps you quickly find the most similar items. It's designed for developers building AI-powered applications that require fast and reliable semantic search, recommendation systems, or anomaly detection.

No commits in the last 6 months.

Use this if you need to deploy a Qdrant vector database that can handle large amounts of data, high query loads, and offers fault tolerance and real-time performance monitoring.

Not ideal if you are looking for a simple, single-node Qdrant setup for small-scale projects or don't require advanced monitoring and scalability features.

vector-database semantic-search recommendation-systems anomaly-detection AI-applications
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 18 / 25

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Stars

30

Forks

12

Language

Python

License

MIT

Last pushed

Mar 30, 2025

Commits (30d)

0

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