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Database & Data Management · head to head

Apache Pinot vs Qdrant

Apache Pinot logo

Apache Pinot

Database & Data Management

Real-time distributed OLAP datastore for analytics

From
Free
Rated
-
Full reviewWebsite
Qdrant logo

Qdrant

Database & Data Management

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

From
Free
Rated
-
Full reviewWebsite

The short version

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

Where they differ

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

Attributes where Apache Pinot and Qdrant differ
AttributeApache PinotQdrant
Pricing modelopen-sourcefreemium
PlatformsLinux, Docker, KubernetesCloud (AWS, GCP, Azure), Kubernetes, Self-hosted, Edge (beta), Serverless (coming)
Founded1999Unknown

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 Apache Pinot

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

Only in Qdrant

Nothing recorded that Apache Pinot does not also cover.

What people use each for

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

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

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

Where each one falls short

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

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

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

Apache Pinot

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

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 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

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 Apache Pinot or Qdrant better?
Neither clearly leads. Apache Pinot 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, Apache Pinot or Qdrant?
Apache Pinot starts at Free and Qdrant at Free.
Does Apache Pinot or Qdrant run on more platforms?
Apache Pinot runs on Linux, Docker, Kubernetes. Qdrant runs on Cloud (AWS, GCP, Azure), Kubernetes, Self-hosted, Edge (beta), Serverless (coming).
Can I use Apache Pinot for free?
Both have a free tier, so you can try either at no cost before committing.
What is Apache Pinot best used for?
Apache Pinot is most often used for sub-second analytics queries on freshly ingested data, user-facing dashboards inside a product, real-time metrics at high ingest rates, petabyte-scale analytics as run at linkedin and uber. Of those, sub-second analytics queries on freshly ingested data and user-facing dashboards inside a product are not what Qdrant is typically brought in for.
What can Apache Pinot do that Qdrant cannot?
Apache Pinot covers Real-time Analytics, Column-oriented, Distributed Processing, SQL Support.
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