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Databases · head to head

Apache Druid vs Immuta

Apache Druid logo

Apache Druid

Databases

Real-time analytics database for sub-second OLAP queries

From
Free
Rated
-
Full reviewWebsite
Immuta logo

Immuta

Databases

Attribute-based access control and masking applied inside Snowflake, Databricks and BigQuery

From
On request
Rated
-
Full reviewWebsite

The short version

  • Only Apache Druid has a free tier, so it costs nothing to try first.
  • Each has a real cost: Apache Druid open-source offering lacks high-availability, distributed architecture, and enterprise security features; Immuta contracts commonly start around one hundred to two hundred thousand US dollars a year for mid-market deployments and exceed five hundred thousand at enterprise scale, which excludes most data teams without a regulatory mandate.
  • They diverge on capability: Apache Druid covers Real-time Ingestion, Immuta covers Attribute-based policy.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Apache Druid and Immuta actually diverge.

Attributes where Apache Druid and Immuta differ
AttributeApache DruidImmuta
Starting priceFreeOn request
Pricing modelopen-sourcequote
Free tierYesNo
PlatformsDocker, Kubernetes, Native deployment (Java-based)Web, API, Cloud
Founded1999Unknown

Identical on both: 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 Druid

  • Real-time Ingestion
  • Sub-second Queries
  • Column-oriented Storage
  • Streaming Integration
  • Approximate Algorithms
  • Flexible Schemas
  • Time-based Partitioning
  • Kafka

Only in Immuta

  • Attribute-based policy
  • Native enforcement
  • Dynamic masking
  • Row-level filtering
  • Purpose-based access
  • Sensitive data tagging
  • Audit logging
  • Multi-platform

What people use each for

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

Apache Druid

  • Real-time analytics platforms ingesting millions of events per second from streaming sourcesnot Immuta
  • Applications requiring sub-second queries over high-cardinality datasets (billions to trillions of rows)not Immuta
  • Time-series and event analysis at massive scale with columnar storage efficiencynot Immuta

Immuta

  • A bank whose Snowflake estate has grown to tens of thousands of roles that no one can review before an auditnot Apache Druid
  • A healthcare analytics team that must let researchers query patient data with identifiers masked unless a specific purpose is recordednot Apache Druid
  • A multinational applying different residency and access rules per jurisdiction to the same tables without duplicating datasetsnot Apache Druid
  • An organisation running both Snowflake and Databricks that wants one policy set rather than two divergent implementationsnot Apache Druid

Where each one falls short

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

Apache Druid

  • Open-source offering lacks high-availability, distributed architecture, and enterprise security features
  • Requires native integration with Apache Kafka or Amazon Kinesis for real-time ingestion; custom integrations need development
  • High-concurrency query support (hundreds of thousands QPS) requires significant cluster infrastructure investment

Immuta

  • Contracts commonly start around one hundred to two hundred thousand US dollars a year for mid-market deployments and exceed five hundred thousand at enterprise scale, which excludes most data teams without a regulatory mandate.
  • Policy is only as good as the data classification underneath it, so an organisation with poorly tagged columns will spend months on classification before Immuta enforces anything useful.
  • Native enforcement means capability varies by platform, and a feature available on Snowflake may be absent or behave differently on BigQuery, which undermines the promise of one policy set everywhere.
  • Adding an access governance layer creates a new dependency in the path to data: a misconfigured policy silently returns fewer rows rather than erroring, and analysts can act on incomplete results without noticing.
  • It governs cloud data platforms, so personal data in operational databases, files and SaaS applications sits outside its scope and needs separate controls, meaning Immuta is rarely the whole answer.

Pricing, plan by plan

Apache Druid

Free

No published plan breakdown. See the Apache Druid review.

Immuta

On request
  • Immuta Platform$undefined/year
    • Attribute-based policy authoring
    • Native enforcement in supported data platforms
    • Dynamic masking and row-level security

Which should you pick?

Choose Apache Druid if

  • You need real-time ingestion.
  • You want to start without paying.
  • You work on Docker, Kubernetes, Native deployment (Java-based).
  • You also want sub-second queries.
Apache Druid review

Choose Immuta if

  • You need attribute-based policy.
  • You work on Web, API, Cloud.
  • You also want native enforcement.
Immuta review

Questions people ask

Is Apache Druid or Immuta better?
Neither clearly leads. Apache Druid starts at Free and Immuta at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Druid or Immuta?
Apache Druid has a free tier; the other does not. Paid plans start at Free for Apache Druid and On request for Immuta.
Does Apache Druid or Immuta run on more platforms?
Apache Druid runs on Docker, Kubernetes, Native deployment (Java-based). Immuta runs on Web, API, Cloud.
Can I use Apache Druid for free?
Yes. Apache Druid has a free tier, so you can try it without paying. Immuta starts at On request.
What is Apache Druid best used for?
Apache Druid is most often used for real-time analytics platforms ingesting millions of events per second from streaming sources, applications requiring sub-second queries over high-cardinality datasets (billions to trillions of rows), time-series and event analysis at massive scale with columnar storage efficiency. Of those, real-time analytics platforms ingesting millions of events per second from streaming sources and applications requiring sub-second queries over high-cardinality datasets (billions to trillions of rows) are not what Immuta is typically brought in for.
What can Apache Druid do that Immuta cannot?
Apache Druid covers Real-time Ingestion, Sub-second Queries, Column-oriented Storage, Streaming Integration. Immuta covers Attribute-based policy, Native enforcement, Dynamic masking, Row-level filtering.

Answered from the vendors’ own pages

Apache Druid: Is Apache Druid free to use?

Apache Druid is an open-source project with no licensing fees. It is licensed under CC BY-SA 4.0, and the Druid name and logo are trademarks of The Apache Software Foundation.

Source
Immuta: Does Immuta sit in the query path?

No. It compiles policies into the data platform's own native controls, so queries run at normal speed through your existing tools.

Apache Druid: Can I use Apache Druid for commercial purposes?

Yes, Apache Druid is open-source software available for commercial use at no cost. The CC BY-SA 4.0 license permits commercial deployment.

Source
Immuta: What does it cost?

Not published. Market data suggests roughly 100,000 to 200,000 US dollars a year for mid-market deployments and considerably more at enterprise scale.

Apache Druid: Where do I find pricing for commercial support or services?

No pricing or support tiers are published on the Apache Druid homepage. For commercial support options, contact the Apache Druid community or consult additional resources beyond the project website.

Source
Immuta: Is Immuta still independent?

Yes. It remains independently owned, unlike several competitors in data access governance that have been acquired.

Immuta: Does it work across more than one warehouse?

Yes, one policy set can target Snowflake, Databricks, BigQuery and Starburst, though enforcement capability varies by platform.

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