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Head-to-head · OLAP Software

Apache Druid vs Apache Pinot

  • Updated Oct 2026
  • Both researched from official sources
  • 3 checks side by side
Higher score Apache Druid #7 in OLAP Software 8.8/10 Open source ✓ 1 of 3 features Visit Apache Druid
Apache Pinot #8 in OLAP Software 8.7/10 Open source ✓ 3 of 3 features Visit Apache Pinot

Apache Druid leads on 0 checks, Apache Pinot on 0, and 3 are even. Who comes out ahead on the 3 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.

Our verdict

  • Highest scoreApache Druid · 8.8/10
  • Most featuresApache Pinot · 3 of 3

Apache Druid scores higher on our rubric for olap software: 8.8 against 8.7 out of 10; our editors rank them #7 and #8.

Apache Druid is the better fit for real-time event analytics. Apache Pinot is the better fit for embedded real-time analytics builders.

  • Apache Druid fits best

    Real-time event analytics

  • Apache Pinot fits best

    Embedded real-time analytics builders

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Side by side

Feature Apache Druid 8.8/10 Visit ↗ Apache Pinot 8.7/10 Visit ↗
At a glance
Editor score 8.8 8.7
Ranking #7 in OLAP Software #8 in OLAP Software
Best for Real-time event analytics Embedded real-time analytics builders
Pricing model Free Free
Starting price Open source Open source
Free plan Not checked yet Not checked yet
Free trial — —
Deployment Self-hosted Self-hosted
Support Community, Docs Community, Docs
Integrations 6 integrations 13 integrations
Built for Mid-market, Enterprise Mid-market, Enterprise
Features Apache Druid 1/3 · Apache Pinot 3/3
Real-time ingestion ✓ ✓
Row-level security Not checked yet ✓ (best)
Embedded analytics Not checked yet ✓ (best)
Specs
Deployment Self_hosted Self_hosted
Query language Sql Sql
Included users Not checked yet Not checked yet
Data source coverage streaming sources, object stores, databases, files Streaming: Kafka, Pulsar, Kinesis; batch: Hadoop, Spark, Amazon S3, Azure ADLS, Google Cloud Storage
Our review
Pros
  • Sub-second OLAP queries for high-cardinality, high-dimensional data
  • Independent scaling for ingestion, queries, and orchestration
  • Streaming, batch loading, SQL, native queries, joins, and bitmap indexes
  • Streams data from Kafka, Pulsar, and Kinesis in real time
  • Combines streaming and batch sources in one table
  • Supports SQL, REST access, joins, upserts, and varied indexes
Cons
  • Self-hosted deployment requires organizations to manage the platform
  • Narrower scope than general cloud data warehouses
  • Row-level security is not verified in the published security documentation
  • Self-hosted deployment requires infrastructure ownership
  • No managed cloud service is included
  • Its focus is real-time OLAP rather than general-purpose analytics
Our verdict

Apache Druid is an open-source, distributed analytics database for large, event-oriented datasets. It is designed for teams building analytical application interfaces and high-concurrency APIs that need sub-second aggregations over…

Read the review →

Apache Pinot is an open-source, distributed OLAP database for user-facing and agent-facing real-time analytics. It is designed for embedded analytics, customer dashboards, metrics APIs, and other high-concurrency analytical applications.…

Read the review →
  1. Apache DruidOLAP Software 8.8Open source
  2. Apache PinotOLAP Software 8.7Open source

Strengths and trade-offs

  • Apache Druid — where it wins

    • Sub-second OLAP queries for high-cardinality, high-dimensional data
    • Independent scaling for ingestion, queries, and orchestration
    • Streaming, batch loading, SQL, native queries, joins, and bitmap indexes

    Where it doesn't

    • Self-hosted deployment requires organizations to manage the platform
    • Narrower scope than general cloud data warehouses
    • Row-level security is not verified in the published security documentation

  • Apache Pinot — where it wins

    • Streams data from Kafka, Pulsar, and Kinesis in real time
    • Combines streaming and batch sources in one table
    • Supports SQL, REST access, joins, upserts, and varied indexes

    Where it doesn't

    • Self-hosted deployment requires infrastructure ownership
    • No managed cloud service is included
    • Its focus is real-time OLAP rather than general-purpose analytics

More comparisons

All OLAP software comparisons → · Full ranking →

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Last updated · How we research and update