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Software · head to head

DuckDB vs Qdrant

DuckDB logo

DuckDB

Software

Fast in-process analytical database

From
Free
Rated
-
Full reviewWebsite
Qdrant logo

Qdrant

Software

High-performance vector database for similarity search and embedding-based retrieval

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: DuckDB client-server setup remains in beta and not recommended for production distributed scenarios; Qdrant free tier extremely limited (0.5 vCPU, 1GB RAM, 4GB disk); suitable only for experiments

Where they differ

Only the attributes on which DuckDB and Qdrant actually diverge.

Attributes where DuckDB and Qdrant differ
AttributeDuckDBQdrant
Pricing modelopen-sourcefreemium
PlatformsLinux, macOS, Windows, WebAssemblyCloud (AWS, GCP, Azure), Kubernetes, Self-hosted, Edge (beta), Serverless (coming)
Founded2019Unknown

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Unknown).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in DuckDB

  • In-process Execution
  • Columnar Storage
  • Vectorized Execution
  • Rich SQL Support
  • Parquet Support
  • CSV/JSON Import
  • Zero Dependencies
  • Python

Only in Qdrant

Nothing recorded that DuckDB does not also cover.

What people use each for

The jobs each tool is most often brought in to do.

DuckDB

  • Analytics and data warehousingnot Qdrant
  • OLAP queries and data explorationnot Qdrant
  • Data science and machine learning workflowsnot Qdrant
  • Multi-format data ingestion and processingnot Qdrant

Qdrant

  • Retrieval-augmented generation (RAG) backends for LLM applicationsnot DuckDB
  • Semantic search across large document corporanot DuckDB
  • Multimodal retrieval (text, images, video) for recommendation systemsnot DuckDB
  • Similarity-based product or content recommendationsnot DuckDB
  • Real-time vector indexing for streaming embedding datanot DuckDB

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

DuckDB

  • Client-server setup remains in beta and not recommended for production distributed scenarios

Qdrant

  • Free tier extremely limited (0.5 vCPU, 1GB RAM, 4GB disk); suitable only for experiments
  • Standard and Premium pricing usage-based; specific costs not published; requires calculator or quote
  • Requires understanding of embeddings and vector search concepts; not suitable for SQL-only teams
  • Early-stage serverless offering (coming soon) suggests maturity gaps in that deployment model

Pricing, plan by plan

DuckDB

Free

No published plan breakdown. See the DuckDB review.

Qdrant

Free
  • FreeFree
    • Single-node cluster
    • 0.5 vCPU
    • 1GB RAM
  • Standard$null/usage-based
    • Dedicated resources
    • Flexible scaling
    • High availability
  • Premium$null/minimum spend
    • SSO and SAML
    • Private VPC links
    • 99.9% uptime SLA

Which should you pick?

Choose DuckDB if

  • You need in-process execution.
  • You want to start without paying.
  • You work on Linux, macOS, Windows, WebAssembly.
  • You also want columnar storage.
DuckDB review

Choose Qdrant if

  • You want to start without paying.
  • You work on Cloud (AWS, GCP, Azure), Kubernetes, Self-hosted, Edge (beta), Serverless (coming).
Qdrant review

Questions people ask

Is DuckDB or Qdrant better?
Neither clearly leads. DuckDB starts at Free and Qdrant at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DuckDB or Qdrant?
DuckDB starts at Free and Qdrant at Free.
Does DuckDB or Qdrant run on more platforms?
DuckDB runs on Linux, macOS, Windows, WebAssembly. Qdrant runs on Cloud (AWS, GCP, Azure), Kubernetes, Self-hosted, Edge (beta), Serverless (coming).
Can I use DuckDB for free?
Both have a free tier, so you can try either at no cost before committing.
What is DuckDB best used for?
DuckDB is most often used for analytics and data warehousing, olap queries and data exploration, data science and machine learning workflows, multi-format data ingestion and processing. Of those, analytics and data warehousing and olap queries and data exploration are not what Qdrant is typically brought in for.
What can DuckDB do that Qdrant cannot?
DuckDB covers In-process Execution, Columnar Storage, Vectorized Execution, Rich SQL Support.
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