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Technology · head to head

Apache Hadoop vs Attio

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
Attio logo

Attio

Technology

The CRM built for the next generation of companies

From
Free
Rated
-
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.; Attio the free plan stops at 3 seats and 50,000 records
  • They diverge on capability: Apache Hadoop covers HDFS, Attio covers Custom data model.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

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

Attributes where Apache Hadoop and Attio differ
AttributeApache HadoopAttio
Pricing modelopen-sourcefreemium
PlatformsWebWeb, Ios, Android, Api
FoundedUnknown2021

Identical on both: starting price (Free), free tier (Yes), 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 Attio

  • Custom data model
  • Flexible views
  • Email integration
  • Calendar sync
  • Automations
  • Mobile app
  • Real-time collaboration
  • Templates

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

Attio

  • Sales pipelinenot Apache Hadoop
  • Customer managementnot Apache Hadoop
  • Deal trackingnot Apache Hadoop
  • Investor relationsnot Apache Hadoop
  • Partnership managementnot 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.

Attio

  • The free plan stops at 3 seats and 50,000 records
  • Outbound email is capped at 200 messages a month on the free plan and 1,000 on Plus
  • Call Intelligence, sequences, advanced reporting and permission controls all require the Pro tier
  • Custom objects are capped at 3 on free, 5 on Plus and 12 on Pro, with unlimited objects reserved for Enterprise
  • File storage is capped at 50 GB on the free and Plus tiers

Pricing, plan by plan

Apache Hadoop

Free

No published plan breakdown. See the Apache Hadoop review.

Attio

Free
  • FreeFree
    • Up to 3 seats
    • 50000 records
    • 3 objects
  • Plus$44/month
    • Up to 10 seats
    • 250000 records
    • 5 objects
  • Pro$99/month
    • Unlimited seats
    • 1000000 records
    • 12 objects
  • EnterpriseFree
    • Custom pricing
    • Unlimited objects
    • Custom record limits

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 Attio if

  • You need custom data model.
  • You want to start without paying.
  • You work on Web, Ios, Android, Api.
  • You also want flexible views.
Attio review

Questions people ask

Is Apache Hadoop or Attio better?
Neither clearly leads. Apache Hadoop starts at Free and Attio at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Hadoop or Attio?
Apache Hadoop starts at Free and Attio at Free.
Does Apache Hadoop or Attio run on more platforms?
Apache Hadoop runs on Web. Attio runs on Web, Ios, Android, 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 Attio is typically brought in for.
What can Apache Hadoop do that Attio cannot?
Apache Hadoop covers HDFS, YARN, MapReduce, HDFS federation and high availability. Attio covers Custom data model, Flexible views, Email integration, Calendar sync.

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.

Attio: How much does Attio cost per user?

Attio's Plus plan is $44/user/month (or $35/month annually with 20% discount). Pro is $99/user/month (or $79/month annually). The Free plan includes up to 3 seats 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.

Attio: What are Attio's seat and record limits for each plan?

Free plan includes up to 3 seats with 50,000 records. Plus supports up to 10 seats with 250,000 records. Pro offers unlimited seats with 1 million records. Enterprise has custom record limits.

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.

Attio: Are there additional costs for Attio beyond the per-user subscription?

Yes, workspace credits are available as add-ons ($70-$475/month depending on volume). Annual billing provides a 20% discount on the base per-user cost.

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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