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Database & Data Management · head to head

Qdrant vs Apache Pinot

Qdrant logo

Qdrant

Database & Data Management

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

From
Free
Rated
-
Full reviewWebsite
Apache Pinot logo

Apache Pinot

Database & Data Management

Real-time distributed OLAP datastore for analytics

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Qdrant free tier extremely limited (0.5 vCPU, 1GB RAM, 4GB disk); suitable only for experiments; Apache Pinot self-hosted and distributed, so running it means operating a cluster rather than consuming a service

Where they differ

Only the attributes on which Qdrant and Apache Pinot actually diverge.

Attributes where Qdrant and Apache Pinot differ
AttributeQdrantApache Pinot
Pricing modelfreemiumopen-source
PlatformsCloud (AWS, GCP, Azure), Kubernetes, Self-hosted, Edge (beta), Serverless (coming)Linux, Docker, Kubernetes
FoundedUnknown1999

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

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 Qdrant

Nothing recorded that Apache Pinot does not also cover.

Only in Apache Pinot

  • Real-time Analytics
  • Column-oriented
  • Distributed Processing
  • SQL Support
  • Pluggable Indexing
  • Star-tree Index
  • Upsert Support
  • Kafka

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 Apache Pinot
  • Semantic search across large document corporanot Apache Pinot
  • Multimodal retrieval (text, images, video) for recommendation systemsnot Apache Pinot
  • Similarity-based product or content recommendationsnot Apache Pinot
  • Real-time vector indexing for streaming embedding datanot Apache Pinot

Apache Pinot

  • Sub-second analytics queries on freshly ingested datanot Qdrant
  • User-facing dashboards inside a productnot Qdrant
  • Real-time metrics at high ingest ratesnot Qdrant
  • Petabyte-scale analytics as run at LinkedIn and Ubernot Qdrant

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

Apache Pinot

  • Self-hosted and distributed, so running it means operating a cluster rather than consuming a service
  • Managed hosting comes from third parties such as StarTree rather than from the project
  • Built for user-facing real-time OLAP, so it is not a general purpose database

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

Apache Pinot

Free
  • Open SourceFree
    • Real-time analytics
    • SQL queries
    • Horizontal scaling

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 Apache Pinot if

  • You need real-time analytics.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes.
  • You also want column-oriented.
Apache Pinot review

Questions people ask

Is Qdrant or Apache Pinot better?
Neither clearly leads. Qdrant starts at Free and Apache Pinot at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Qdrant or Apache Pinot?
Qdrant starts at Free and Apache Pinot at Free.
Does Qdrant or Apache Pinot run on more platforms?
Qdrant runs on Cloud (AWS, GCP, Azure), Kubernetes, Self-hosted, Edge (beta), Serverless (coming). Apache Pinot runs on Linux, Docker, Kubernetes.
Can I use Qdrant for free?
Both have a free tier, so you can try either at no cost before committing.
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 Apache Pinot is typically brought in for.
What can Qdrant do that Apache Pinot cannot?
Apache Pinot covers Real-time Analytics, Column-oriented, Distributed Processing, SQL Support.
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