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Apache Hadoop vs Zeta

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
Rated
-
Full reviewWebsite
Zeta logo

Zeta

Technology

Cloud native credit card processing and core banking from Bhavin Turakhia's Zeta

From
On request
Rated
-
Full reviewWebsite

The short version

  • Only Apache Hadoop has a free tier, so it costs nothing to try first.
  • 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.; Zeta it competes against card processors with decades of production track record, and in card processing an outage is a public event, so a shorter operational history is a genuine risk factor rather than a technicality.
  • They diverge on capability: Apache Hadoop covers HDFS, Zeta covers Tachyon card processing.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

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

Attributes where Apache Hadoop and Zeta differ
AttributeApache HadoopZeta
Starting priceFreeOn request
Pricing modelopen-sourcequote
Free tierYesNo
PlatformsWebWeb, API, Cloud, iOS, Android

Identical on both: user rating (Not yet rated), category (Technology).

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 Zeta

  • Tachyon card processing
  • Real time authorisation
  • Rewards and offers engine
  • Core banking modules
  • Programme configuration
  • Mobile and web SDKs
  • Fraud and controls
  • Cloud deployment

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

Zeta

  • A United States bank whose card platform makes launching a new rewards product a multi quarter vendor projectnot Apache Hadoop
  • An issuer that wants authorisation level controls and real time data rather than end of day filesnot Apache Hadoop
  • A large fintech launching a credit card programme at scale with custom product logicnot Apache Hadoop
  • A bank consolidating card and deposit processing onto one modern platformnot 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.

Zeta

  • It competes against card processors with decades of production track record, and in card processing an outage is a public event, so a shorter operational history is a genuine risk factor rather than a technicality.
  • Contracts are enterprise scale and quoted with volume minimums, which puts it out of reach of small issuers who would otherwise benefit most from modern tooling.
  • A card portfolio migration runs twelve to twenty four months at minimum, during which the issuer runs two platforms and pays for both.
  • Zeta is a processor rather than a licence holder, so network membership, BIN sponsorship and regulatory obligations remain entirely with the issuer.
  • Public references for large live United States production volumes are fewer than the announcements imply, so diligence should insist on active account counts and uptime history rather than partnership press releases.

Pricing, plan by plan

Apache Hadoop

Free

No published plan breakdown. See the Apache Hadoop review.

Zeta

On request
  • Tachyon platform$undefined/year
    • Quoted per institution, commonly on active accounts or transaction volume
    • Implementation for a card portfolio migration measured in quarters to years
    • Minimum volume commitments typical on enterprise contracts

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 Zeta if

  • You need tachyon card processing.
  • You work on Web, API, Cloud, iOS, Android.
  • You also want real time authorisation.
Zeta review

Questions people ask

Is Apache Hadoop or Zeta better?
Neither clearly leads. Apache Hadoop starts at Free and Zeta at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Hadoop or Zeta?
Apache Hadoop has a free tier; the other does not. Paid plans start at Free for Apache Hadoop and On request for Zeta.
Does Apache Hadoop or Zeta run on more platforms?
Apache Hadoop runs on Web. Zeta runs on Web, API, Cloud, iOS, Android.
Can I use Apache Hadoop for free?
Yes. Apache Hadoop has a free tier, so you can try it without paying. Zeta starts at On request.
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 Zeta is typically brought in for.
What can Apache Hadoop do that Zeta cannot?
Apache Hadoop covers HDFS, YARN, MapReduce, HDFS federation and high availability. Zeta covers Tachyon card processing, Real time authorisation, Rewards and offers engine, Core banking modules.

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.

Zeta: Which Zeta is this?

The banking technology company founded by Bhavin Turakhia, which builds the Tachyon card processing and core banking platform. Not any similarly named payroll or accounting product.

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.

Zeta: What is its strongest use case?

United States credit card issuing and processing, where legacy platforms make product changes slow and expensive.

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.

Zeta: Does Zeta provide the BIN or licence?

No. It processes. Network membership, BIN sponsorship and regulatory obligations stay with the issuer.

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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