Softwr

Database & Data Management · head to head

Qdrant vs Ninox

Qdrant logo

Qdrant

Database & Data Management

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

From
Free
Rated
-
N

Ninox

Database & Data Management

The database for teams

From
On request
Rated
-

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; Ninox paid plans are priced per user starting around 25 euros per month, and offline desktop and mobile access is limited to the higher Business and Enterprise tiers

Where they differ

Only the attributes on which Qdrant and Ninox actually diverge.

Attributes where Qdrant and Ninox differ
AttributeQdrantNinox
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 Ninox
  • Semantic search across large document corporanot Ninox
  • Multimodal retrieval (text, images, video) for recommendation systemsnot Ninox
  • Similarity-based product or content recommendationsnot Ninox
  • Real-time vector indexing for streaming embedding datanot Ninox

Ninox

No use cases recorded yet. See the Ninox 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

Ninox

  • Paid plans are priced per user starting around 25 euros per month, and offline desktop and mobile access is limited to the higher Business and Enterprise tiers

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

Ninox

On request

No published plan breakdown. See the Ninox 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).

Choose Ninox if

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

Questions people ask

Is Qdrant or Ninox better?
Neither clearly leads. Qdrant starts at Free and Ninox at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Qdrant or Ninox?
Qdrant has a free tier; the other does not. Paid plans start at Free for Qdrant and On request for Ninox.
Does Qdrant or Ninox run on more platforms?
Qdrant runs on Cloud (AWS, GCP, Azure), Kubernetes, Self-hosted, Edge (beta), Serverless (coming). Ninox runs on Web.
Can I use Qdrant for free?
Yes. Qdrant has a free tier, so you can try it without paying. Ninox 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 Ninox is typically brought in for.

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