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Head-to-head · Vector Databases

Qdrant vs Upstash Vector

  • Updated Oct 2026
  • Both researched from official sources
  • 5 checks side by side
Higher score Qdrant #7 in Vector Databases 8.7/10 Free plan Free plan✓ 3 of 3 features Visit Qdrant
Upstash Vector #15 in Vector Databases 7.9/10 Free plan Free plan✓ 3 of 3 features Visit Upstash Vector

Qdrant leads on 1 check, Upstash Vector on 0, and 4 are even. Who comes out ahead on the 5 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.

Our verdict

  • Highest scoreQdrant · 8.7/10
  • Free planboth

Qdrant scores higher on our rubric for vector databases: 8.7 against 7.9 out of 10; our editors rank them #7 and #15.

On deployment, Qdrant gives you Both where Upstash Vector offers Cloud. Qdrant leads on maximum dimensions: 65535 dimensions versus 3072 dimensions.

Qdrant is the better fit for modern teams wanting open hybrid search. Upstash Vector is the better fit for low-cost serverless vector workloads.

  • Qdrant fits best

    Modern teams wanting open hybrid search

  • Upstash Vector fits best

    Low-cost serverless vector workloads

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Side by side

Feature Qdrant 8.7/10 Visit ↗ Upstash Vector 7.9/10 Visit ↗
At a glance
Editor score 8.7 7.9
Ranking #7 in Vector Databases #15 in Vector Databases
Best for Modern teams wanting open hybrid search Low-cost serverless vector workloads
Pricing model Free plan + paid Free plan + paid
Starting price — $60/mo
Free plan ✓ ✓
Free trial — —
Deployment Cloud, Self-hosted Cloud
Platforms Web, Windows, macOS, Linux Web
Support Email, Tickets, Community, Docs Email, Community, Docs
Compliance SOC 2, HIPAA, GDPR GDPR
Built for Small business, Mid-market, Enterprise Solo, Small business, Mid-market, Enterprise
Features Qdrant 3/3 · Upstash Vector 3/3
Hybrid search ✓ ✓
Metadata filtering ✓ ✓
Sparse vectors ✓ ✓
Specs
Deployment Both Cloud
Maximum dimensions 65535 dimensions (best) 3072 dimensions
Index types HNSW; sparse vector index; payload index; filterable HNSW DiskANN, FreshDiskANN
SDK languages Python, JavaScript/TypeScript, Rust, Go, .NET, Java Python, TypeScript, Go, PHP
Our review
Pros
  • Hybrid dense and sparse search with metadata filtering
  • Open-source self-hosting plus managed cloud deployment
  • Multivectors, named vectors, REST, and gRPC APIs
  • Free plan includes 10,000 daily queries and updates
  • Supports dense, sparse, and hybrid vector indexes
  • REST API, namespaces, filtering, and DiskANN search
Cons
  • The Free Tier is limited to a single node
  • Free resources are limited to 0.5 vCPU, 1 GB RAM, and 4 GB disk
  • Paid cloud tiers use usage-based pricing rather than fixed plan amounts
  • Free plan allows only 1 GB of total data
  • Verified integration coverage is limited to the Vercel AI SDK
  • Higher-capacity plan pricing is not shown in the published plan details
Our verdict

Qdrant is an open-source vector search engine and vector database for developers building semantic search, recommendations, retrieval-augmented generation, and other AI applications. It supports self-hosted deployment and Qdrant Cloud,…

Read the review →

Upstash Vector is a fully managed, serverless vector database for developers building semantic search, retrieval-augmented generation, and other AI applications. It supports REST access and official SDKs for Python, TypeScript, Go, and…

Read the review →
  1. QdrantVector Databases 8.7Free plan
  2. Upstash VectorVector Databases 7.9Free plan

Strengths and trade-offs

  • Qdrant — where it wins

    • Hybrid dense and sparse search with metadata filtering
    • Open-source self-hosting plus managed cloud deployment
    • Multivectors, named vectors, REST, and gRPC APIs

    Where it doesn't

    • The Free Tier is limited to a single node
    • Free resources are limited to 0.5 vCPU, 1 GB RAM, and 4 GB disk
    • Paid cloud tiers use usage-based pricing rather than fixed plan amounts

  • Upstash Vector — where it wins

    • Free plan includes 10,000 daily queries and updates
    • Supports dense, sparse, and hybrid vector indexes
    • REST API, namespaces, filtering, and DiskANN search

    Where it doesn't

    • Free plan allows only 1 GB of total data
    • Verified integration coverage is limited to the Vercel AI SDK
    • Higher-capacity plan pricing is not shown in the published plan details

More comparisons

All vector databases comparisons → · Full ranking →

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Last updated · How we research and update