Software · head to head
H2O.ai vs RapidMiner
The short version
- Each has a real cost: 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; RapidMiner rapidMiner is now a Siemens product: rapidminer.com redirects to a Siemens product page and the former Altair page redirects there too
- They diverge on capability: H2O.ai covers Distributed computing, RapidMiner covers Visual workflows.
Where they differ
Only the attributes on which H2O.ai and RapidMiner actually diverge.
| Attribute | H2O.ai | RapidMiner |
|---|---|---|
| Platforms | Web, Cloud | Linux, Mac, Windows, Web |
| Founded | 2011 | 2007 |
Identical on both: starting price (Free), pricing model (freemium), free tier (Yes), user rating (Not yet rated), category (Unknown).
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 H2O.ai
- Distributed computing
- Feature engineering
- Model explainability
- Time series forecasting
- JDBC
Only in RapidMiner
- Visual workflows
- Data preparation
- Model deployment
- Text mining
- Cloud platforms
Both cover
- AutoML
- Spark
- Hadoop
- Python
- R
- Linux support
- Mac support
- Windows support
- Web support
What people use each for
The jobs each tool is most often brought in to do.
H2O.ai
- Distributed in-memory machine learning over large datasetsnot RapidMiner
- Training and productionising models from R or Python against a shared H2O clusternot RapidMiner
RapidMiner
- Visual drag and drop machine learning model buildingnot H2O.ai
- Data preparation and cleansing before modellingnot H2O.ai
- Deploying and scoring predictive models in an enterprise settingnot H2O.ai
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
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
RapidMiner
- RapidMiner is now a Siemens product: rapidminer.com redirects to a Siemens product page and the former Altair page redirects there too
- Pricing is by quote only: the product page publishes no rate, no licensing unit and no minimum, offering only a Contact us button
- The product is now one component of a six product portfolio alongside Graph Studio, SLC, Monarch, Panopticon and Knowledge Studio
Pricing, plan by plan
H2O.ai
Free- H2O-3 Open SourceFree
- Core algorithms
- AutoML
- Community support
- Driverless AIFree
- Automatic feature engineering
- Model explainability
- Enterprise support
RapidMiner
Free- FreeFree
- 10,000 data rows
- 1 logical processor
- ProfessionalFree
- Unlimited data
- Full features
- Support
Which should you pick?
Choose H2O.ai if
- You need distributed computing.
- You want to start without paying.
- You work on Web, Cloud.
- You also want feature engineering.
Choose RapidMiner if
- You need visual workflows.
- You want to start without paying.
- You work on Linux, Mac, Windows, Web.
- You also want data preparation.
Questions people ask
- Is H2O.ai or RapidMiner better?
- Neither clearly leads. H2O.ai starts at Free and RapidMiner at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, H2O.ai or RapidMiner?
- H2O.ai starts at Free and RapidMiner at Free.
- Does H2O.ai or RapidMiner run on more platforms?
- H2O.ai runs on Web, Cloud. RapidMiner runs on Linux, Mac, Windows, Web.
- Can I use H2O.ai for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is H2O.ai best used for?
- H2O.ai is most often used for distributed in-memory machine learning over large datasets, training and productionising models from r or python against a shared h2o cluster. Of those, distributed in-memory machine learning over large datasets and training and productionising models from r or python against a shared h2o cluster are not what RapidMiner is typically brought in for.
- What can H2O.ai do that RapidMiner cannot?
- H2O.ai covers Distributed computing, Feature engineering, Model explainability, Time series forecasting. RapidMiner covers Visual workflows, Data preparation, Model deployment, Text mining. Both handle AutoML, Spark, Hadoop, Python.
Answered from the vendors’ own pages
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.
SourceH2O.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