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Database & Data Management · head to head

Qdrant vs Knack

Qdrant logo

Qdrant

Database & Data Management

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

From
Free
Rated
-
Full reviewWebsite
K

Knack

Database & Data Management

Build online databases and apps without code

From
On request
Rated
-
Full reviewWebsite

The short version

  • Only Qdrant has a free tier, so it costs nothing to try first.
  • Each has a real cost: Qdrant free tier extremely limited (0.5 vCPU, 1GB RAM, 4GB disk); suitable only for experiments; Knack plans are priced by number of records and objects rather than users, ranging from $110 to $300 per month as data volume grows

Where they differ

Only the attributes on which Qdrant and Knack actually diverge.

Attributes where Qdrant and Knack differ
AttributeQdrantKnack
Starting priceFreeOn request
Pricing modelfreemiumsubscription
Free tierYesNo
PlatformsCloud (AWS, GCP, Azure), Kubernetes, Self-hosted, Edge (beta), Serverless (coming)Web

Identical on both: user rating (Not yet rated), category (Database & Data Management).

What people use each for

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

Qdrant

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

Knack

No use cases recorded yet. See the Knack review.

Where each one falls short

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

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

Knack

  • Plans are priced by number of records and objects rather than users, ranging from $110 to $300 per month as data volume grows

Pricing, plan by plan

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

Knack

On request

No published plan breakdown. See the Knack review.

Which should you pick?

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

Choose Knack if

Nothing in the data separates Knack from Qdrant on the points above - pick on price and on how each one feels to use.

Knack review

Questions people ask

Is Qdrant or Knack better?
Neither clearly leads. Qdrant starts at Free and Knack at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Qdrant or Knack?
Qdrant has a free tier; the other does not. Paid plans start at Free for Qdrant and On request for Knack.
Does Qdrant or Knack run on more platforms?
Qdrant runs on Cloud (AWS, GCP, Azure), Kubernetes, Self-hosted, Edge (beta), Serverless (coming). Knack runs on Web.
Can I use Qdrant for free?
Yes. Qdrant has a free tier, so you can try it without paying. Knack starts at On request.
What is Qdrant best used for?
Qdrant is most often used for retrieval-augmented generation (rag) backends for llm applications, semantic search across large document corpora, multimodal retrieval (text, images, video) for recommendation systems, similarity-based product or content recommendations. Of those, retrieval-augmented generation (rag) backends for llm applications and semantic search across large document corpora are not what Knack is typically brought in for.
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Related pages

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