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Machine Learning & Data Science · head to head

Azure Machine Learning vs H2O.ai

Azure Machine Learning logo

Azure Machine Learning

Machine Learning & Data Science

Enterprise-grade machine learning service

From
Free
Rated
-
Full reviewWebsite
H2O.ai logo

H2O.ai

Machine Learning & Data Science

AI Cloud for building and deploying AI applications

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Azure Machine Learning requires knowledge of Azure ecosystem and integration with other Azure services; 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: Azure Machine Learning covers Automated ML, H2O.ai covers AutoML.

Where they differ

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

Attributes where Azure Machine Learning and H2O.ai differ
AttributeAzure Machine LearningH2O.ai
Pricing modelusage-basedfreemium
PlatformsAzure CloudWeb, Cloud
Founded19752011

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Machine Learning & Data Science).

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 Azure Machine Learning

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

Only in H2O.ai

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

Both cover

  • Web support

What people use each for

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

Azure Machine Learning

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

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

Where each one falls short

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

Azure Machine Learning

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

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

Azure Machine Learning

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

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 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

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 Azure Machine Learning or H2O.ai better?
Neither clearly leads. Azure Machine Learning starts at Free and H2O.ai at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Azure Machine Learning or H2O.ai?
Azure Machine Learning starts at Free and H2O.ai at Free.
Does Azure Machine Learning or H2O.ai run on more platforms?
Azure Machine Learning runs on Azure Cloud. H2O.ai runs on Web, Cloud.
Can I use Azure Machine Learning for free?
Both have a free tier, so you can try either at no cost before committing.
What is Azure Machine Learning best used for?
Azure Machine Learning is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what H2O.ai is typically brought in for.
What can Azure Machine Learning do that H2O.ai cannot?
Azure Machine Learning covers Automated ML, Designer (drag-and-drop), Notebooks, MLOps. H2O.ai covers AutoML, Distributed computing, Feature engineering, Model explainability. Both handle Web support.

Answered from the vendors’ own pages

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: 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: 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
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: 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
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