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Databases · head to head

Apache Pinot vs Dremio

Apache Pinot logo

Apache Pinot

Databases

Real-time distributed OLAP datastore for analytics

From
Free
Rated
-
Full reviewWebsite
Dremio logo

Dremio

Databases

SQL query engine and lakehouse layer over Iceberg tables in object storage

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; Dremio reflections consume compute and storage to build and refresh continuously, so a team that enables them widely discovers that background maintenance rather than user queries drives the DCU bill.
  • They diverge on capability: Apache Pinot covers Real-time Analytics, Dremio covers Arrow-based execution.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

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

Attributes where Apache Pinot and Dremio differ
AttributeApache PinotDremio
Pricing modelopen-sourcePer Dremio Compute Unit consumed
PlatformsLinux, Docker, KubernetesLinux, Kubernetes, Cloud, Docker
Founded1999Unknown

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

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 Dremio

  • Arrow-based execution
  • Reflections
  • Semantic layer
  • Iceberg catalogue
  • Federated queries
  • Autonomous management
  • Fine-grained access control
  • BI connectors

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 Dremio
  • User-facing dashboards inside a productnot Dremio
  • Real-time metrics at high ingest ratesnot Dremio
  • Petabyte-scale analytics as run at LinkedIn and Ubernot Dremio

Dremio

  • A company with petabytes of Parquet in S3 that wants BI dashboards without duplicating it into a warehousenot Apache Pinot
  • A data platform team standardising on Apache Iceberg and needing a SQL engine plus catalogue that does not lock the tables innot Apache Pinot
  • An analytics group accelerating slow lake queries with Reflections instead of hand-built aggregate tablesnot Apache Pinot
  • A regulated enterprise that must keep data on premises but wants a modern lakehouse SQL layernot 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

Dremio

  • Reflections consume compute and storage to build and refresh continuously, so a team that enables them widely discovers that background maintenance rather than user queries drives the DCU bill.
  • Self-managing Dremio on Kubernetes requires real platform engineering capacity for tuning executors, memory and coordinator sizing, and it is not comparable in effort to running a managed warehouse.
  • The Community Edition lacks the security and governance features most enterprises require, so the free tier is a trial path rather than a viable production option for regulated buyers.
  • Dremio Cloud is AWS-first, which leaves Azure and Google Cloud customers on the self-managed path with the operational burden that entails.
  • Query performance without Reflections on raw, poorly laid out files is often unremarkable, so the promise of querying the lake as is depends on file layout work you still have to do.

Pricing, plan by plan

Apache Pinot

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

Dremio

Free
  • Community EditionFree
    • Self-managed on your own hardware
    • SQL engine and semantic layer
    • No vendor support
  • Dremio Cloud$0.2/hour
    • Billed at $0.20 per Dremio Compute Unit
    • Includes query execution, Reflections and background processing
    • 400 dollar trial credit for 30 days
  • Enterprise$undefined/year
    • Self-managed on Kubernetes, on premises or any cloud
    • Enterprise security, SSO and governance
    • Vendor support with 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 Dremio if

  • You need arrow-based execution.
  • You want to start without paying.
  • You work on Linux, Kubernetes, Cloud, Docker.
  • You also want reflections.
Dremio review

Questions people ask

Is Apache Pinot or Dremio better?
Neither clearly leads. Apache Pinot starts at Free and Dremio at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Pinot or Dremio?
Apache Pinot starts at Free and Dremio at Free.
Does Apache Pinot or Dremio run on more platforms?
Apache Pinot runs on Linux, Docker, Kubernetes. Dremio runs on Linux, Kubernetes, Cloud, Docker.
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 Dremio is typically brought in for.
What can Apache Pinot do that Dremio cannot?
Apache Pinot covers Real-time Analytics, Column-oriented, Distributed Processing, SQL Support. Dremio covers Arrow-based execution, Reflections, Semantic layer, Iceberg catalogue.

Answered from the vendors’ own pages

Apache Pinot: How much does Apache Pinot cost?

Apache Pinot is free and open-source. It is provided under the Apache License, which allows free use, modification, and distribution.

Source
Dremio: How is Dremio Cloud billed?

At 0.20 US dollars per Dremio Compute Unit, which counts query execution, Reflection building and platform overhead, not just user queries.

Apache Pinot: Is Apache Pinot free for commercial use?

Yes. Apache Pinot is licensed under the Apache License, which explicitly permits commercial use at no cost.

Source
Dremio: Is there a free version?

Yes, a Community Edition you self-manage, but it omits the enterprise security and governance features and comes with no support.

Apache Pinot: Can I run Apache Pinot locally or with Docker?

Yes. Apache Pinot offers a Docker quickstart and free downloads of the latest version (1.5.1 at the time of the page). You are responsible for hosting and infrastructure.

Source
Dremio: Does it lock in my data?

No, tables stay in Apache Iceberg or Parquet in your own object storage and can be read by Spark, Trino or other engines.

Apache Pinot: Are there restrictions on how I can use Apache Pinot?

The Apache License permits unrestricted use, but requires retention of license notices and statements. No usage limits or feature restrictions are enforced.

Source
Dremio: Do I still need a warehouse?

Often not for analytics, but Dremio is not a transactional store and high-concurrency operational serving is not its strength.

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