CompareBestAI
Join UsJoin Us
Qdrant
Free PlanOpen Source

Qdrant

by Qdrant

Open-source vector DB with powerful managed cloud.

Reviewed September 2026by CBAI Editorial Team
8.0/10

Score

4.0 out of 5 · our score
Compare
Developer

Our verdict

Qdrant stands out in 2026 as a developer-friendly, open-source vector database with a clear path from prototyping to enterprise scale. The Apache-2.0 core lets teams self-host at zero license cost, while Qdrant Cloud provides a generous free single-node cluster and a usage-based Standard tier that meters exactly what you use (vCPU, RAM, storage, backups, inference). Search quality is strong with HNSW, robust metadata filtering, and native hybrid dense+sparse retrieval. Recent additions like GPU-accelerated indexing, TurboQuant quantization, and Qdrant Cloud Inference broaden its appeal. Premium brings SSO, private VPC links, Multi-AZ and stricter SLAs, addressing enterprise needs. Downsides: there’s no simple flat monthly price, Premium requires a minimum spend, and some advanced deployment options require sales engagement. Overall, Qdrant offers excellent value and technical depth, with one of the most transparent paths from OSS to managed production among vector DBs.

Overview

Qdrant is an open‑source (Apache‑2.0) Rust-based vector database offering high-performance similarity search and hybrid retrieval. Made by Qdrant, it powers RAG, semantic search, and recommendations at scale with HNSW, payload filtering, and quantization. Qdrant Cloud adds a permanently free tier, usage-based Standard, and Premium with SSO, VPC links, and higher SLAs, plus Hybrid/Private Cloud options for regulated deployments.

Score breakdown

Overall score

8.0/10
Output quality8.0/10
Ease of use7.5/10
Value for money8.5/10
Features & tools8.5/10
API & integrations9.0/10
Support & docs7.0/10

Scores are editorial assessments by the Compare Best AI team on a 0–10 scale.

Expert review

C

CBAI Editorial Team

Compare Best AI · Editorial Team

## Overview

How we tested

Days tested

7 days

Tasks evaluated

  • ·Ingest and query 1M 768-dim vectors with payload filters
  • ·Hybrid dense+sparse RAG search against a docs corpus
  • ·Shard replication, failover, and snapshot/restore exercise
  • ·GPU-accelerated indexing and TurboQuant memory benchmark

Method

Compared against Pinecone and Milvus using identical inputs

Reviewer

CBAI Editorial Team

Plans & pricing

Free Tier

$0
  • Free forever
Most Popular

Standard

Usage-based
  • Usage-based pricing

Premium

Custom
  • Contact sales

Pricing may vary by region. Always verify on the vendor's website.

Feature comparison

FeatureQdrantPineconeMilvus
Core
Open-source self-hosted option (Apache-2.0)
Search
Hybrid dense+sparse search (native fusion)
Filtering
Advanced metadata filtering at query time
Performance
GPU-accelerated indexing
APIs & SDKs
REST and gRPC APIs + official multi-language SDKs
Security/Network
Private VPC links (managed cloud)
Reliability
Multi-AZ managed HA option
Included Partial / add-on Not included

Is it right for you?

Good fit for

AI application developers

Fast to prototype with the free cloud tier, then scale using usage-based Standard without re-architecting.

Platform teams

Strong automation surface (APIs, Terraform, clients) and HA/backup options make it fit for platform provisioning.

Enterprises with compliance needs

Premium adds SSO, VPC links, Multi‑AZ, and custom‑key encryption on AWS/GCP.

Cost-sensitive startups

Apache‑2.0 self-hosting and clear hourly metering control spend from day one.

Less suited for

Teams needing a fixed monthly SaaS price

Qdrant Cloud Standard is metered hourly by resources, not a flat per-seat fee.

Ultra-locked down on-prem with no internet

Possible via Private Cloud, but requires a sales engagement and custom deployment.

User reviews

4.0

Editorial score

5
48%
4
28%
3
6%
2
4%
1
0%

Distribution is estimated from our editorial score. Verified user reviews coming soon.

Use cases

Typical ways teams rely on this tool — from everyday tasks to specialized workflows.

  • Retrieval-augmented generation (RAG)
  • Semantic product search
  • Personalized recommendations
  • Multimodal hybrid search

Integrations

Reported connectors

Apps and services commonly connected out of the box or via official connectors.

  • LangChain
  • LlamaIndex
  • Terraform

Privacy & compliance

Security & data practices

Highlights we track from the vendor's documentation. Always confirm current terms, subprocessors, and regional policies on their official site.

  • Encryption at rest and in transit
  • Custom-key disk encryption (AWS/GCP)
  • SSO (Premium)

Details

Category

Developer

Price

  • Open Source (self-hosted) $0
  • Cloud Free $0
  • Cloud Standard usage-based hourly (metered by vCPU, RAM, storage, backup storage, inference tokens)
  • Cloud Premium custom (minimum spend required)
  • Hybrid Cloud custom
  • Private Cloud custom

Free version

Yes

Best for

  • Prototyping vector search with a free managed cluster
  • Self-hosted deployments under Apache‑2.0
  • Hybrid dense+sparse retrieval for RAG
  • Regulated workloads needing Private/Hybrid Cloud

Frequently asked questions

Qdrant

Qdrant

Developer

Ready to get started?

Visit the Qdrant website to explore plans and start your free trial.

Was this page helpful?

Compare Best AI may earn a commission when you click links on this page. This does not influence our editorial scores or recommendations. Advertiser disclosure