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Apache Hadoop vs Hookdeck

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
Hookdeck logo

Hookdeck

Developer Tools

Event gateway that receives, queues, retries and replays inbound webhooks

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.; Hookdeck pricing meters delivered events, so fan-out multiplies the bill: one inbound event routed to four services counts as four deliveries.
  • They diverge on capability: Apache Hadoop covers HDFS, Hookdeck covers Ingest and persist.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

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

Attributes where Apache Hadoop and Hookdeck differ
AttributeApache HadoopHookdeck
Pricing modelopen-sourcePer month by delivered event count
PlatformsWebWeb, Linux, macOS, Windows
CategoryTechnologyDeveloper Tools

Identical on both: starting price (Free), 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 Hookdeck

  • Ingest and persist
  • Automatic retries
  • Filters and fan-out
  • Transformations
  • Local development CLI
  • Rate limiting

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

Hookdeck

  • A payments integration where losing a Stripe event during a deploy causes an order to go unfulfillednot Apache Hadoop
  • Fanning one provider webhook out to several internal services without each subscribing separatelynot Apache Hadoop
  • Debugging a partner integration by replaying the exact failing payload after shipping a fixnot Apache Hadoop
  • Receiving production-shaped webhooks on a developer laptop without running a public tunnelnot 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.

Hookdeck

  • Pricing meters delivered events, so fan-out multiplies the bill: one inbound event routed to four services counts as four deliveries.
  • Free-tier retention is three days, which is shorter than the time it typically takes to notice a failing integration, so the payloads needed for a replay are often already gone.
  • It becomes a single point of failure in front of every third-party integration, and an outage there means every provider webhook queues or fails at once.
  • The transformation layer runs JavaScript in a constrained environment, so anything that needs a database lookup or an external call has to happen downstream instead.
  • For a team already running Kafka or SQS the value is mostly the console and the replay UI, which is a hard cost to justify against infrastructure they already operate.

Pricing, plan by plan

Apache Hadoop

Free

No published plan breakdown. See the Apache Hadoop review.

Hookdeck

Free
  • DeveloperFree
    • Up to ten thousand events per month
    • Three-day retention
    • One user
  • Team$39/month
    • Ten thousand events included
    • Unlimited users
    • Pay as you go metering above the included events
  • Growth$499/month
    • Ten thousand events included plus metered usage
    • Thirty-day retention
    • Uptime and latency SLAs
  • Enterprise$undefined/year
    • Negotiated event volume
    • Custom retention
    • Dedicated 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 Hookdeck if

  • You need ingest and persist.
  • You want to start without paying.
  • You work on Web, Linux, macOS, Windows.
  • You also want automatic retries.
Hookdeck review

Questions people ask

Is Apache Hadoop or Hookdeck better?
Neither clearly leads. Apache Hadoop starts at Free and Hookdeck at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Hadoop or Hookdeck?
Apache Hadoop starts at Free and Hookdeck at Free.
Does Apache Hadoop or Hookdeck run on more platforms?
Apache Hadoop runs on Web. Hookdeck runs on Web, Linux, macOS, Windows.
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 Hookdeck is typically brought in for.
What can Apache Hadoop do that Hookdeck cannot?
Apache Hadoop covers HDFS, YARN, MapReduce, HDFS federation and high availability. Hookdeck covers Ingest and persist, Automatic retries, Filters and fan-out, Transformations.

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.

Hookdeck: Is there a free plan?

Yes, ten thousand events a month with three-day retention and one user.

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.

Hookdeck: How is usage counted?

By delivered events, so a single inbound webhook fanned out to three destinations counts as three.

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.

Hookdeck: Can I replay a failed webhook?

Yes, individually or in bulk from the console, with the original payload.

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.

Hookdeck: Does it work for outbound webhooks too?

Yes, the same queueing, retry and observability applies to webhooks you send.

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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