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Apache Hadoop vs Buildkite

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
Buildkite logo

Buildkite

Developer Tools

CI/CD pipelines that run on your own compute

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.; Buildkite free plan caps at 5 users and 10 concurrent jobs, with 2,000 Linux vCPU minutes per month and 30 day build retention
  • Prices and features above were last checked on 30 August 2026.

Where they differ

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

Attributes where Apache Hadoop and Buildkite differ
AttributeApache HadoopBuildkite
Pricing modelopen-sourcesubscription
CategoryTechnologyDeveloper Tools

Identical on both: starting price (Free), free tier (Yes), platforms (Web), 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 Buildkite

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 Buildkite
  • Running Spark or Flink under YARN on hardware you already own, using HDFS as the storage layernot Buildkite
  • Keeping long-lived regulated archives on infrastructure entirely within your own data centres and legal jurisdictionnot Buildkite
  • Maintaining legacy Hive and MapReduce workloads during a staged migration to a lakehouse or cloud platformnot Buildkite

Buildkite

  • CI/CD pipeline automationnot Apache Hadoop
  • Test execution at scalenot Apache Hadoop
  • Deployment automationnot 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.

Buildkite

  • Free plan caps at 5 users and 10 concurrent jobs, with 2,000 Linux vCPU minutes per month and 30 day build retention
  • Pro plan is $30 per active user per month, capped at 50 users, with only 10 of the up to 250 concurrent agents included before extra usage
  • Enterprise plan enforces a 30 user minimum even though pricing itself is custom
  • Hosted compute beyond included minutes is metered at $0.004 per vCPU minute on Linux and $0.02 per vCPU minute on Mac

Pricing, plan by plan

Apache Hadoop

Free

No published plan breakdown. See the Apache Hadoop review.

Buildkite

Free
  • FreeFree
    • Up to 5 users
    • 10 concurrent jobs
    • 2000 Linux vCPU minutes monthly
  • Pro$30/month
    • Up to 50 users
    • 250 concurrent agents (10 included)
    • 4000 Linux vCPU minutes monthly
  • Enterprise$null/custom
    • Unlimited users (30 minimum)
    • Custom usage limits
    • Full platform access

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 Buildkite if

  • You want to start without paying.
Buildkite review

Questions people ask

Is Apache Hadoop or Buildkite better?
Neither clearly leads. Apache Hadoop starts at Free and Buildkite at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Hadoop or Buildkite?
Apache Hadoop starts at Free and Buildkite at Free.
Does Apache Hadoop or Buildkite run on more platforms?
Both run on Web, so platform support will not decide this one for you.
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 Buildkite is typically brought in for.
What can Apache Hadoop do that Buildkite 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.

Buildkite: Can I use Buildkite without paying?

Yes, Buildkite offers a free plan that includes up to 5 users, 10 concurrent jobs, 2000 Linux vCPU minutes monthly, and 250k test executions per month at no cost.

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.

Buildkite: What happens if I exceed my included compute minutes on Buildkite?

Hosted agent compute is charged separately at $0.004 per Linux vCPU minute and $0.02 per Mac vCPU minute, billed to the second with no minimums.

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.

Buildkite: Do I need an annual commitment for Buildkite's Pro plan?

No, Buildkite's Pro plan is billed monthly at $30 per active user with no long-term contract required. All tiers include a 30-day all-access trial.

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.

Buildkite: What user limits apply to each Buildkite plan?

Free plan supports up to 5 users, Pro plan supports up to 50 users, and Enterprise plan provides unlimited users with a 30-user minimum.

Source
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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