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Qdrant

Qdrant is a vector similarity search engine and vector database for storing, searching, and managing vectors with associated payload.

  • AI
  • Databases
  • Tools & Utilities
Qdrant is a vector similarity search engine and vector database for storing, searching, and managing vectors with associated payload. It provides a production-ready API for similarity search, extended payload filtering, and semantic matching, making it useful for AI applications, faceted search, and self-hosted retrieval services.

Platform availability

Available on 4 of 6 install platforms

Also on Docker Hub and GitHub

Health score

79/100 Good

Maintained
100last commit 32 days ago
Popular
9134,870 GitHub stars
Easy to install
654 install platforms, install notes, Docker image
Light to run
2032 GB minimum RAM, runs on ARM
How is this calculated?

A 0-100 score computed nightly from four factors: maintained (40%: recent commits and steady activity), popular (25%: GitHub stars, log scale), easy to install (20%: platforms, install notes, setup guides, Docker image) and light to run (15%: minimum RAM, ARM support). Factors without data are left out and the rest are rescaled.

Availability: platform listings confirmed today, links checked 8 days ago

GitHub stars
34,870
Open issues
745
Last commit
2026-09-03
Latest release
v1.19.1
License
Apache-2.0
Activity
stale

Checked 7 days ago - source: GitHub (qdrant/qdrant)

Resources & Compatibility

Minimum requirements: 32 GB RAM, 12 CPU core(s), 500 GB disk. ARM (e.g. Raspberry Pi) is supported.

Checked 7 days ago - source: Docker Hub image tags and published docs

First-install notes

  • Start Qdrant with Docker Run `docker run -p 6333:6333 qdrant/qdrant` to launch Qdrant and expose port 6333, which is where Qdrant listens for API connections. This simple setup is intentionally open, so if you plan to reach it from outside your own network, review the security guide first to avoid accidental public access. source

Fetched 7 days ago - each note links to its source

Alternatives (12)

  • Algolia - Algolia helps product teams connect their users with information by providing the building blocks they need to create fast, relevant, perso…
  • Elasticsearch - Elasticsearch is a distributed search and analytics engine used for full-text search, log analysis, and vector search.
  • Golem - Golem is a global, open sourced, decentralized supercomputer that anyone can access.
  • Manticore search - Open source search server designed to be fast, scalable and with powerful and accurate full-text search capabilities derived from Sphinx se…
  • OpenSearch - OpenSearch is a scalable, flexible, and extensible open-source software suite for search, analytics, and observability applications derived…
  • elasti - KubeElasti is a Kubernetes-native solution that offers scale-to-zero functionality when there is no traffic and automatic scale up to 1 whe…
  • elastic search
  • elasticsearch 5 - Elasticsearch 5 is a distributed search and analytics engine that stores indexed data centrally for web-based querying.
  • meilisearch - An open-source, fast, and hyper-relevant search engine that fits effortlessly into your projects.
  • solr - Solr is the popular, blazing-fast, open source enterprise search platform built on Apache Lucene.
  • toshi moto - Toshi Moto is a watch-only Bitcoin wallet designed for secure portfolio monitoring and transaction tracking.
  • typesense - Typesense is an open-source, typo-tolerant search engine focused on simplicity, performance and developer ergonomics.

Checked 4 days ago - source: AlternativeTo

Common questions

Which port should I expose for Qdrant?

The documented Docker command exposes port 6333, which is where Qdrant listens for API connections.

How do I secure a self-hosted Qdrant instance?

Enable TLS, create an Admin API key, and restrict consumers with a Read-Only key or collection-scoped JWT tokens.

Can I run Qdrant on Windows without Docker?

You can install or build Qdrant on Windows without Docker by setting up Rust, Git, protoc, and LLVM, then cloning the repository.

Is there a Docker Compose setup that persists Qdrant data?

A community Docker Compose project provides persistent storage and management scripts for self-hosting Qdrant.

What should I check when self-hosted Qdrant won't connect or return results?

Check connection refused, vector dimension mismatch, empty search results, gRPC unavailable, and memory issues.

Answers sourced from github.com, github.com, prismix.dev, qdrant.tech, stackoverflow.com

Community

Collected 7 days ago - public community threads