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Apache Hadoop vs Keycloak

Apache Hadoop logo

Apache Hadoop

Technology

The original open source framework for distributed storage and batch processing on commodity servers, now largely a legacy platform.

From
Free
Free plan
Yes
Full reviewWebsite
Keycloak logo

Keycloak

Developer Tools

Open-source identity and access management server.

From
Free
Free plan
Yes
Full reviewWebsite

The short version

  • Each has a real cost: Apache Hadoop the free vendor distributions no longer exist: Cloudera's CDH and Hortonworks' HDP have reached end of support and the successor CDP is subscription-only, so running Hadoop without paying now means assembling, testing and security-patching Apache releases yourself.; Keycloak requires self-hosted deployment and operational expertise to install, configure and maintain
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Apache Hadoop and Keycloak actually diverge.

Attributes where Apache Hadoop and Keycloak differ
AttributeApache HadoopKeycloak
PlatformsWebSelf-hosted, Docker, Kubernetes, Linux, Windows, API
CategoryTechnologyDeveloper Tools

Identical on both: starting price (Free), pricing model (open-source), free tier (Yes), user rating (Not yet rated).

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 Hadoop

  • HDFS
  • YARN
  • MapReduce
  • HDFS federation and high availability
  • Kerberos security
  • Rack awareness
  • S3A and object store connectors
  • Ecosystem compatibility

Only in Keycloak

Nothing recorded that Apache Hadoop does not also cover.

What people use each for

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

Apache Hadoop

  • Operating an existing multi-petabyte on-premises estate where data residency or egress costs rule out moving to cloud object storagenot Keycloak
  • Running Spark or Flink under YARN on hardware you already own, using HDFS as the storage layernot Keycloak
  • Keeping long-lived regulated archives on infrastructure entirely within your own data centres and legal jurisdictionnot Keycloak
  • Maintaining legacy Hive and MapReduce workloads during a staged migration to a lakehouse or cloud platformnot Keycloak

Keycloak

  • Organisations requiring self-hosted identity infrastructure for compliance or data residencynot Apache Hadoop
  • Companies with existing LDAP/Active Directory systems needing federated authenticationnot Apache Hadoop
  • Open-source projects and communities requiring free IAM without licensing costsnot Apache Hadoop
  • Enterprises building custom identity workflows requiring fine-grained authorisationnot Apache Hadoop
  • Teams with sufficient operational expertise to manage infrastructurenot Apache Hadoop

Where each one falls short

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

Apache Hadoop

  • The free vendor distributions no longer exist: Cloudera's CDH and Hortonworks' HDP have reached end of support and the successor CDP is subscription-only, so running Hadoop without paying now means assembling, testing and security-patching Apache releases yourself.
  • HDFS couples storage to compute, so adding capacity means buying whole nodes with CPU and memory you may not need, and the entire industry moved to object storage precisely because it lets the two be bought separately.
  • The NameNode holds all filesystem metadata in memory, so a cluster with tens of millions of small files exhausts heap long before it exhausts disk, and the remedy is a file compaction job that somebody has to write, schedule and own indefinitely.
  • Operating it is a distinct specialism covering Kerberos, YARN queue tuning, JVM garbage collection and the compatibility matrix between Hive, HBase, Ranger, Oozie and the core, and an upgrade touches all of them at once rather than one at a time.
  • MapReduce is maintained for compatibility rather than actively developed, and new work goes to Spark or Flink, so a job written against MapReduce today is written against an API that will not gain anything further.
  • Hiring is against you: the talent pool has moved to cloud data platforms over the past decade, so a Hadoop estate increasingly depends on a small number of individuals, which makes it a succession risk before it is a technical one.

Keycloak

  • Requires self-hosted deployment and operational expertise to install, configure and maintain
  • No managed cloud option provided by Red Hat; organisations must operate infrastructure themselves or use third-party distributions
  • Clustering and high-availability configurations require additional operational knowledge
  • Community support only; commercial support requires third-party vendors or distributions

Pricing, plan by plan

Apache Hadoop

Free

No published plan breakdown. See the Apache Hadoop review.

Keycloak

Free
  • Open-sourceFree
    • Full platform functionality
    • Self-hosted deployment
    • Community support

Which should you pick?

Choose Apache Hadoop if

  • You need hdfs.
  • You want to start without paying.
  • You also want yarn.
Apache Hadoop review

Choose Keycloak if

  • You want to start without paying.
  • You work on Self-hosted, Docker, Kubernetes, Linux, Windows, API.
Keycloak review

Questions people ask

Is Apache Hadoop or Keycloak better?
Neither clearly leads. Apache Hadoop starts at Free and Keycloak at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Hadoop or Keycloak?
Apache Hadoop starts at Free and Keycloak at Free.
Does Apache Hadoop or Keycloak run on more platforms?
Apache Hadoop runs on Web. Keycloak runs on Self-hosted, Docker, Kubernetes, Linux, Windows, API.
Can I use Apache Hadoop for free?
Both have a free tier, so you can try either at no cost before committing.
What is Apache Hadoop best used for?
Apache Hadoop is most often used for operating an existing multi-petabyte on-premises estate where data residency or egress costs rule out moving to cloud object storage, running spark or flink under yarn on hardware you already own, using hdfs as the storage layer, keeping long-lived regulated archives on infrastructure entirely within your own data centres and legal jurisdiction, maintaining legacy hive and mapreduce workloads during a staged migration to a lakehouse or cloud platform. Of those, operating an existing multi-petabyte on-premises estate where data residency or egress costs rule out moving to cloud object storage and running spark or flink under yarn on hardware you already own, using hdfs as the storage layer are not what Keycloak is typically brought in for.
What can Apache Hadoop do that Keycloak cannot?
Apache Hadoop covers HDFS, YARN, MapReduce, HDFS federation and high availability.

Answered from the vendors’ own pages

Apache Hadoop: Is Hadoop dead?

No, but it is legacy. Large on-premises HDFS estates still run and are still supported, and Spark and Flink still run on YARN. What has ended is Hadoop as a default choice for new platforms, which now start on object storage.

Keycloak: What protocols does Keycloak support?

Keycloak supports OpenID Connect, OAuth 2.0 and SAML 2.0 protocols for authentication and authorisation.

Source
Apache Hadoop: Can I still get a free packaged distribution?

Not a maintained one. CDH and HDP reached end of support and Cloudera's CDP is a paid subscription. The remaining free route is building and patching Apache releases yourself, which is a real engineering commitment.

Keycloak: Can Keycloak integrate with existing user directories?

Yes. Keycloak supports user federation with LDAP and Active Directory systems, allowing organisations to leverage existing user directories.

Source
Apache Hadoop: Do I need Hadoop to run Spark?

No. Spark runs standalone, on Kubernetes and on managed cloud services, and reads object storage directly. Many Spark deployments include Hadoop client libraries for the filesystem connectors without running a Hadoop cluster at all.

Keycloak: Is Keycloak free?

Yes. Keycloak is fully open-source and free to deploy and use. No licensing fees are required.

Source
Apache Hadoop: What replaced HDFS?

Object storage, typically S3 or a compatible system, combined with an open table format such as Apache Iceberg or Delta Lake. Apache Ozone exists as an object store within the Hadoop ecosystem for organisations staying on-premises.

Apache Hadoop: Is it cheaper than the cloud?

It can be at multi-petabyte scale with steady, predictable utilisation, particularly where egress charges would be large. Include the staffing cost honestly, because the specialist operators a Hadoop cluster requires are scarce and therefore expensive.

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