Qdrant
Verified Oct 2, 2026 ActiveOpen-source vector search engine written in Rust, available self-hosted or as a managed cloud for RAG and recommendation apps.
Listed on EffectHub ·
Pricing
- Pricing model
- Freemium
The engine is free under Apache 2.0. Qdrant Cloud has a free forever single-node tier (0.5 vCPU, 1 GB RAM, 4 GB disk), a usage-based Standard tier and a Premium tier with a minimum spend; no fixed dollar price is listed, only a pricing calculator.
Use tool ↗About Qdrant
Qdrant stores vectors alongside JSON metadata and answers similarity queries with rich filtering, including nested, text and geo filters. It supports dense and sparse vectors for hybrid search, multivector storage, and quantization to reduce memory use. You can run the Apache-licensed engine yourself, use the managed Qdrant Cloud on AWS, Azure or GCP, or run managed clusters on your own infrastructure through Hybrid Cloud. Developers use it for retrieval-augmented generation, recommendations and semantic search, and the Berlin company behind it also offers an edge build in beta.
- Platforms
- Web · API
- API
- Yes
- Last verified
- Oct 2, 2026
Verified sources
- Cloud tiers: free forever single-node, usage-based Standard, Premium with minimum spend, plus Hybrid and Private Cloudqdrant.tech ↗
- Rust vector search engine with metadata filters, hybrid search and multivectors; SOC 2 and HIPAA claimsqdrant.tech ↗
- Founders André Zayarni and Andrey Vasnetsov began the project in 2021; terms name Qdrant Solutions GmbH in Berlinqdrant.tech ↗
Is Qdrant legit?
We don’t label tools safe or unsafe. Below are the records we checked ourselves, each with the date we read it.
- Last checked
- Oct 2, 2026The site answered
- On the market since
- 2021The vendor's own material, read by us
- Operated by
- Qdrant Solutions GmbH, GermanyOur research, card verified Oct 2, 2026
Pros & cons of Qdrant
A mature, well-documented vector database that is easy to start with locally and scales to managed or private deployments. It is a strong pick when you want open-source control and fine-grained metadata filtering. Paid cost is usage-based and not quoted as a simple number, so estimate it with the vendor's calculator before committing.
Pros
- Apache 2.0 engine with a free forever cloud tier
- Native hybrid search with dense and sparse vectors
- Deployable on your own servers, in Qdrant Cloud, or in your own cloud
- SOC 2 and HIPAA compliance listed on the homepage
Cons
- Standard and Premium cloud pricing is usage-based with no quoted starting price
- The free tier is a single small node suited to prototypes only
- Self-hosting means you handle scaling, backups and upgrades
Best for
- Teams building RAG or semantic search who want an open-source, self-hostable store
- Applications that need heavy metadata filtering alongside vector similarity
- Regulated companies that need to run managed clusters in their own cloud
Not for
- Teams that want a single database for relational data and vectors without extra services
- Buyers who need a flat, predictable monthly price printed on the pricing page
Watch out: The free tier is one small node for testing; production traffic needs the usage-billed Standard tier, so run the pricing calculator on your expected vector count first.
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Qdrant head-to-head
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