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Technology · head to head

Apache Hadoop vs Figma

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
Figma logo

Figma

Technology

The collaborative interface design tool

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.; Figma no offline editing capability, can only view and create new files when disconnected
  • They diverge on capability: Apache Hadoop covers HDFS, Figma covers Real-time collaboration.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

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

Attributes where Apache Hadoop and Figma differ
AttributeApache HadoopFigma
Pricing modelopen-sourceUnknown
PlatformsWebWeb, macOS, Windows, iOS, Android
FoundedUnknown2012

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 Figma

  • Real-time collaboration
  • Vector networks
  • Auto-layout
  • Components & variants
  • Prototyping
  • Design systems
  • Developer handoff
  • Version control

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

Figma

  • UI/UX designnot Apache Hadoop
  • Design systemsnot Apache Hadoop
  • Prototypingnot Apache Hadoop
  • Design collaborationnot Apache Hadoop
  • Developer handoffnot 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.

Figma

  • No offline editing capability, can only view and create new files when disconnected
  • Mobile apps are read-only, cannot edit designs on iOS or Android
  • No self-hosted option, requires cloud connectivity and internet access
  • Performance degradation with large files containing thousands of layers
  • Library components and unloaded pages not accessible offline

Pricing, plan by plan

Apache Hadoop

Free

No published plan breakdown. See the Apache Hadoop review.

Figma

Free
  • StarterFree
    • Unlimited drafts
    • 3 Figma files
    • 3 FigJam boards
  • Professional$12/month
    • Unlimited files and folders
    • Team libraries
    • Advanced prototyping
  • Organization$55/month
    • Unlimited teams
    • Shared libraries
    • Design system theming
  • Enterprise$90/month
    • Custom workspaces
    • API access
    • SCIM seat management

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 Figma if

  • You need real-time collaboration.
  • You want to start without paying.
  • You work on Web, macOS, Windows, iOS, Android.
  • You also want vector networks.
Figma review

Questions people ask

Is Apache Hadoop or Figma better?
Neither clearly leads. Apache Hadoop starts at Free and Figma at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Hadoop or Figma?
Apache Hadoop starts at Free and Figma at Free.
Does Apache Hadoop or Figma run on more platforms?
Apache Hadoop runs on Web. Figma runs on Web, macOS, Windows, iOS, Android.
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 Figma is typically brought in for.
What can Apache Hadoop do that Figma cannot?
Apache Hadoop covers HDFS, YARN, MapReduce, HDFS federation and high availability. Figma covers Real-time collaboration, Vector networks, Auto-layout, Components & variants.

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.

Figma: What's included in Figma's free tier?

Figma's Starter plan is free forever and includes unlimited drafts, up to 3 Figma files, 3 FigJam boards, core design features (vector editing, auto layout, components, prototyping), basic developer handoff (inspect), and 150 AI credits per day up to 500 per month. Maximum 2 editors per file.

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.

Figma: Does Figma work offline?

Figma has very limited offline support. You can create one new file and edit currently loaded pages, but cannot open previously created files, access new pages, search for library components, or see real-time collaboration. Changes are cached locally for up to 30 days and sync when you reconnect.

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.

Figma: Can you self-host Figma?

No. Figma is a closed, cloud-only platform with no option to self-host or run on your own servers.

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.

Figma: What export formats does Figma support?

Figma exports to PNG, JPEG, SVG (at 1x scale only), and PDF (at 1x scale only). Export settings allow customization of resolution, quality, and scale.

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.

Figma: What platforms does Figma support?

Figma is available as a web app (all platforms), desktop apps for macOS and Windows, and mobile apps for iOS and Android. Linux users can access Figma through the web browser only.

Source
Figma: What are Figma's integrations?

Figma integrates with Slack, Microsoft Teams, Jira, Asana, Linear, Notion, VS Code, Zapier, and hundreds of other tools. Integration categories include collaboration, project management, developer handoff, prototyping, and AI/code generation.

Source
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