Softwr

Software · head to head

H2O.ai vs Azure Machine Learning

H2O.ai logo

H2O.ai

Software

AI Cloud for building and deploying AI applications

From
Free
Rated
-
Full reviewWebsite
Azure Machine Learning logo

Azure Machine Learning

Software

Enterprise-grade machine learning service

From
Free
Rated
-
Full reviewWebsite

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; Azure Machine Learning requires knowledge of Azure ecosystem and integration with other Azure services
  • They diverge on capability: H2O.ai covers AutoML, Azure Machine Learning covers Automated ML.

Where they differ

Only the attributes on which H2O.ai and Azure Machine Learning actually diverge.

Attributes where H2O.ai and Azure Machine Learning differ
AttributeH2O.aiAzure Machine Learning
Pricing modelfreemiumusage-based
PlatformsWeb, CloudAzure Cloud
Founded20111975

Identical on both: starting price (Free), 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

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

Only in Azure Machine Learning

  • Automated ML
  • Designer (drag-and-drop)
  • Notebooks
  • MLOps
  • Model registry
  • Azure Blob Storage
  • Azure DevOps
  • Power BI

Both cover

  • 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 Azure Machine Learning
  • Training and productionising models from R or Python against a shared H2O clusternot Azure Machine Learning

Azure Machine Learning

  • Machine learningnot H2O.ai
  • Data analysisnot H2O.ai
  • Model trainingnot H2O.ai
  • Predictive analyticsnot 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

Azure Machine Learning

  • Requires knowledge of Azure ecosystem and integration with other Azure services
  • Compute resources for training and inference generate separate charges

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

Azure Machine Learning

Free
  • Free TierFree
    • Limited compute
    • Basic features
  • Pay-as-you-go$0.05/hour
    • Full platform
    • All compute options
    • Enterprise features

Which should you pick?

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

Choose Azure Machine Learning if

  • You need automated ml.
  • You want to start without paying.
  • You work on Azure Cloud.
  • You also want designer (drag-and-drop).
Azure Machine Learning review

Questions people ask

Is H2O.ai or Azure Machine Learning better?
Neither clearly leads. H2O.ai starts at Free and Azure Machine Learning at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, H2O.ai or Azure Machine Learning?
H2O.ai starts at Free and Azure Machine Learning at Free.
Does H2O.ai or Azure Machine Learning run on more platforms?
H2O.ai runs on Web, Cloud. Azure Machine Learning runs on Azure Cloud.
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 Azure Machine Learning is typically brought in for.
What can H2O.ai do that Azure Machine Learning cannot?
H2O.ai covers AutoML, Distributed computing, Feature engineering, Model explainability. Azure Machine Learning covers Automated ML, Designer (drag-and-drop), Notebooks, MLOps. Both handle Web support.

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.

Source
Azure Machine Learning: Does Azure Machine Learning have any platform licensing fees?

No, Azure Machine Learning carries no extra cost. You only pay for the underlying compute resources utilized during model training or inference.

Source
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
Azure Machine Learning: What AutoML capabilities does Azure Machine Learning provide?

Azure Machine Learning supports automated model creation for classification, regression, vision, and natural language processing tasks.

Source
Azure Machine Learning: Does Azure ML support language model fine-tuning?

Yes, Azure Machine Learning supports fine-tuning of foundation models from providers including OpenAI, Meta, Hugging Face, and Cohere.

Source
Azure Machine Learning: What MLOps features are included?

Azure ML includes end-to-end pipeline automation with CI/CD capabilities, managed endpoints for model deployment, and monitoring tools.

Source
Azure Machine Learning: Can I access foundation models from multiple vendors?

Yes, Azure Machine Learning provides access to a model catalog with foundation models from Microsoft, OpenAI, Hugging Face, Meta, and Cohere.

Source
ShareXLinkedInRedditWhatsAppEmail

Related pages

More on H2O.ai

More on Azure Machine Learning

Keep looking

Other head to heads