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Business Intelligence · head to head

Anaplan vs H2O.ai

Anaplan logo

Anaplan

Business Intelligence

Connected planning platform with an in-memory calculation engine for large multidimensional models

From
On request
Rated
-
Full reviewWebsite
H2O.ai logo

H2O.ai

Machine Learning

AI Cloud for building and deploying AI applications

From
Free
Rated
-
Full reviewWebsite

The short version

  • Only H2O.ai has a free tier, so it costs nothing to try first.
  • Each has a real cost: Anaplan workspace is licensed by memory consumed, so a model that grows as the business adds SKUs, regions or scenarios generates a bill increase without a single new user being added, and teams end up optimising models for licence cost rather than clarity.; H2O.ai java is always required to run H2O-3 even when working from R or Python, and only a 64-bit JRE or JDK is supported
  • They diverge on capability: Anaplan covers Hyperblock calculation engine, H2O.ai covers AutoML.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Anaplan and H2O.ai actually diverge.

Attributes where Anaplan and H2O.ai differ
AttributeAnaplanH2O.ai
Starting priceOn requestFree
Pricing modelquotefreemium
Free tierNoYes
PlatformsWeb, iOSWeb, Cloud
CategoryBusiness IntelligenceMachine Learning
FoundedUnknown2011

Identical on both: 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 Anaplan

  • Hyperblock calculation engine
  • Connected planning
  • Scenario and versioning
  • Model builder
  • Anaplan PlanIQ
  • Workflow and approvals
  • Application lifecycle management
  • Data integration

Only in H2O.ai

  • AutoML
  • Distributed computing
  • Feature engineering
  • Model explainability
  • Time series forecasting
  • Spark
  • Hadoop
  • Python

What people use each for

The jobs each tool is most often brought in to do.

Anaplan

  • Sales territory and quota planning across thousands of reps where a change to segmentation must reflow quota immediatelynot H2O.ai
  • Demand and supply planning at SKU and location level for a manufacturer with tens of thousands of itemsnot H2O.ai
  • Workforce planning that ties headcount, cost and capacity to a revenue plan across dozens of business unitsnot H2O.ai
  • Replacing a spreadsheet estate where the master planning model has become too large and too fragile for Excel to open reliablynot H2O.ai

H2O.ai

  • Distributed in-memory machine learning over large datasetsnot Anaplan
  • Training and productionising models from R or Python against a shared H2O clusternot Anaplan

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Anaplan

  • Workspace is licensed by memory consumed, so a model that grows as the business adds SKUs, regions or scenarios generates a bill increase without a single new user being added, and teams end up optimising models for licence cost rather than clarity.
  • Model building requires certified Anaplan modellers using a proprietary formula language, and the labour market for that skill is small, so most customers stay dependent on a systems integrator long after go-live.
  • Thoma Bravo took the company private in 2022 in a $10.7bn deal, and customers have since reported firmer renewal terms; a private-equity owner optimising for cash flow is a real factor in a multi-year planning contract.
  • Native reporting and visualisation are weak for anything beyond planning grids, so most customers push data out to Power BI or Tableau for executive reporting, adding another tool and another latency point.
  • Implementations are long. A connected planning programme across finance and supply chain routinely runs six to eighteen months before the first production plan, which is difficult to justify when the business wants a forecast this quarter.

H2O.ai

  • Java is always required to run H2O-3 even when working from R or Python, and only a 64-bit JRE or JDK is supported
  • Supported Java versions stop at Java SE 17; newer versions only run by forcing an unsupported version flag and are guaranteed for experiments rather than production
  • H2O-3 only supports numpy below version 2, so a numpy 2 environment must be downgraded
  • Supported Python versions are limited to 3.7 through 3.11
  • The Flow web UI requires an internet browser and is the only graphical interface

Pricing, plan by plan

Anaplan

On request
  • Anaplan$undefined/year
    • Licensed by user tier and by workspace capacity
    • Workspace charged on memory consumed by models, independent of user count
    • Multi-year enterprise agreements are the norm

H2O.ai

Free
  • H2O-3 Open SourceFree
    • Core algorithms
    • AutoML
    • Community support
  • Driverless AIFree
    • Automatic feature engineering
    • Model explainability
    • Enterprise support

Which should you pick?

Choose Anaplan if

  • You need hyperblock calculation engine.
  • You work on Web, iOS.
  • You also want connected planning.
Anaplan review

Choose H2O.ai if

  • You need automl.
  • You want to start without paying.
  • You work on Web, Cloud.
  • You also want distributed computing.
H2O.ai review

Questions people ask

Is Anaplan or H2O.ai better?
Neither clearly leads. Anaplan starts at On request and H2O.ai at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Anaplan or H2O.ai?
H2O.ai has a free tier; the other does not. Paid plans start at On request for Anaplan and Free for H2O.ai.
Does Anaplan or H2O.ai run on more platforms?
Anaplan runs on Web, iOS. H2O.ai runs on Web, Cloud.
Can I use H2O.ai for free?
Yes. H2O.ai has a free tier, so you can try it without paying. Anaplan starts at On request.
What is Anaplan best used for?
Anaplan is most often used for sales territory and quota planning across thousands of reps where a change to segmentation must reflow quota immediately, demand and supply planning at sku and location level for a manufacturer with tens of thousands of items, workforce planning that ties headcount, cost and capacity to a revenue plan across dozens of business units, replacing a spreadsheet estate where the master planning model has become too large and too fragile for excel to open reliably. Of those, sales territory and quota planning across thousands of reps where a change to segmentation must reflow quota immediately and demand and supply planning at sku and location level for a manufacturer with tens of thousands of items are not what H2O.ai is typically brought in for.
What can Anaplan do that H2O.ai cannot?
Anaplan covers Hyperblock calculation engine, Connected planning, Scenario and versioning, Model builder. H2O.ai covers AutoML, Distributed computing, Feature engineering, Model explainability.

Answered from the vendors’ own pages

Anaplan: Why is Anaplan expensive even when user counts are low?

Because workspace is licensed on the memory your models consume as well as on users. Large models cost money regardless of how many people log in.

H2O.ai: Is H2O open source and free?

Yes. H2O-3 OSS is free and Apache-licensed, designed for self-managed and experimental workflows. H2O.ai also offers enterprise cloud solutions with additional features.

Source
Anaplan: Do we need a systems integrator?

Almost always for the first implementation. The proprietary modelling language and the scale of typical models make an experienced partner or an internal certified team effectively mandatory.

H2O.ai: How many companies use H2O's open source platform?

Over 18,000 companies across Finance, Insurance, Healthcare, Retail, Telco, Sales, and Marketing use H2O's open-source machine learning platform.

Source
Anaplan: Who owns Anaplan?

Thoma Bravo, which took it private in 2022 for $10.7bn.

Anaplan: Can it replace our BI tool?

No. It is a planning and calculation platform; most customers still export to Power BI or Tableau for reporting and dashboards.

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