Technology · head to head
Apache Hadoop vs Plane

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
- -
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.; Plane self-hosted Community edition requires managing your own Docker/Kubernetes infra plus your own PostgreSQL, Redis, and S3-compatible/GCS/MinIO storage; no single-binary install
- They diverge on capability: Apache Hadoop covers HDFS, Plane covers Issue tracking.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Apache Hadoop and Plane actually diverge.
| Attribute | Apache Hadoop | Plane |
|---|---|---|
| Pricing model | open-source | freemium |
| Platforms | Web | Web, iOS, Android, macOS, Windows |
| Founded | Unknown | 2022 |
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 Plane
- Issue tracking
- Cycles (Sprints)
- Modules
- Views & layouts
- Pages (Docs)
- Analytics
- API access
- Webhooks
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 Plane
- Running Spark or Flink under YARN on hardware you already own, using HDFS as the storage layernot Plane
- Keeping long-lived regulated archives on infrastructure entirely within your own data centres and legal jurisdictionnot Plane
- Maintaining legacy Hive and MapReduce workloads during a staged migration to a lakehouse or cloud platformnot Plane
Plane
- Project and task management with cycles, modules, epics, and initiativesnot Apache Hadoop
- Documentation and knowledge management via workspace wiki tied to project worknot Apache Hadoop
- Sprint planning and issue triagenot Apache Hadoop
- Cross-functional collaboration with analytics and dashboardsnot Apache Hadoop
- Migration target from Jira, Linear, Monday, ClickUp, or Asananot 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.
Plane
- Self-hosted Community edition requires managing your own Docker/Kubernetes infra plus your own PostgreSQL, Redis, and S3-compatible/GCS/MinIO storage; no single-binary install
- Cloud Free tier caps at 12 users and 500 AI credits per seat per month
- Substantial feature gating by tier: custom work item types, workspace wiki, time tracking, dashboards, initiatives, teamspaces, and integrations require Pro or above; LDAP, granular access control, and multi-workflow approvals require Enterprise Grid
- Guest-to-paid-member ratio capped at 1:5 on the Pro plan
Pricing, plan by plan
Apache Hadoop
FreeNo published plan breakdown. See the Apache Hadoop review.
Plane
Free- FreeFree
- 500 AI credits per seat
- Max 12 users
- Unlimited projects
- Pro$6/seat per month
- 1,000 AI credits per seat
- Unlimited users
- Custom work item types
- Business$13/seat per month
- 2,000 AI credits per seat
- Unlimited users
- Project templates, recurring work items
- Enterprise Grid$null/mo
- Flexible AI credit allocation
- Private deployments
- Granular access control
Which should you pick?
Choose Apache Hadoop if
- You need hdfs.
- You want to start without paying.
- You also want yarn.
Choose Plane if
- You need issue tracking.
- You want to start without paying.
- You work on Web, iOS, Android, macOS, Windows.
- You also want cycles (sprints).
Questions people ask
- Is Apache Hadoop or Plane better?
- Neither clearly leads. Apache Hadoop starts at Free and Plane at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Apache Hadoop or Plane?
- Apache Hadoop starts at Free and Plane at Free.
- Does Apache Hadoop or Plane run on more platforms?
- Apache Hadoop runs on Web. Plane runs on Web, iOS, Android, 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 Plane is typically brought in for.
- What can Apache Hadoop do that Plane cannot?
- Apache Hadoop covers HDFS, YARN, MapReduce, HDFS federation and high availability. Plane covers Issue tracking, Cycles (Sprints), Modules, Views & layouts.
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.
Plane: Does Plane offer a free plan?
Yes, Plane's free tier includes 500 AI credits per seat, support for up to 12 users, and access to projects, work items, cycles, modules, layouts, views, estimates, and pages.
SourceApache 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.
Plane: How much does Plane Pro cost?
Plane Pro costs $6/seat per month and saves 25% when billed annually. It includes 1,000 AI credits per seat, unlimited users, and access to custom work item types, wiki, time tracking, and integrations.
SourceApache 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.
Plane: What is the difference between Plane's paid tiers?
Pro ($6/seat/month) includes 1,000 AI credits and workspace wiki. Business ($13/seat/month) adds 2,000 AI credits, project templates, and recurring work items. Enterprise Grid offers custom pricing with multiple workflows and LDAP support.
SourceApache 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.
Related pages
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