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Machine Learning & Data Science · head to head

H2O.ai vs Apache Spark MLlib

H2O.ai logo

H2O.ai

Machine Learning & Data Science

AI Cloud for building and deploying AI applications

From
Free
Rated
-
Full reviewWebsite
Apache Spark MLlib logo

Apache Spark MLlib

Machine Learning & Data Science

Scalable machine learning on Apache Spark

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; Apache Spark MLlib apache Spark MLlib is Apache 2.0 licensed and free with no paid tier from the Apache project itself; SLA-backed support has to be sourced from a third party such as a managed Spark vendor rather than from Apache.
  • They diverge on capability: H2O.ai covers AutoML, Apache Spark MLlib covers Classification.

Where they differ

Only the attributes on which H2O.ai and Apache Spark MLlib actually diverge.

Attributes where H2O.ai and Apache Spark MLlib differ
AttributeH2O.aiApache Spark MLlib
Pricing modelfreemiumopen-source
PlatformsWeb, CloudLinux, macOS, Windows
Founded20111999

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 H2O.ai

  • AutoML
  • Distributed computing
  • Model explainability
  • Time series forecasting
  • Spark
  • Python
  • R
  • JDBC

Only in Apache Spark MLlib

  • Classification
  • Regression
  • Clustering
  • Collaborative filtering
  • Apache Spark
  • Kafka
  • Databricks
  • AWS EMR

Both cover

  • Feature engineering
  • Hadoop
  • Linux support
  • Mac support
  • Windows 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 Apache Spark MLlib
  • Training and productionising models from R or Python against a shared H2O clusternot Apache Spark MLlib

Apache Spark MLlib

  • Large-scale distributed machine learning on Spark clustersnot H2O.ai
  • Classification and regression with decision trees, random forests, gradient-boosted treesnot H2O.ai
  • Clustering with K-means and Gaussian Mixture Modelsnot 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

Apache Spark MLlib

  • Apache Spark MLlib is Apache 2.0 licensed and free with no paid tier from the Apache project itself; SLA-backed support has to be sourced from a third party such as a managed Spark vendor rather than from Apache.

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

Apache Spark MLlib

Free

No published plan breakdown. See the Apache Spark MLlib review.

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 Apache Spark MLlib if

  • You need classification.
  • You want to start without paying.
  • You work on Linux, macOS, Windows.
  • You also want regression.
Apache Spark MLlib review

Questions people ask

Is H2O.ai or Apache Spark MLlib better?
Neither clearly leads. H2O.ai starts at Free and Apache Spark MLlib at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, H2O.ai or Apache Spark MLlib?
H2O.ai starts at Free and Apache Spark MLlib at Free.
Does H2O.ai or Apache Spark MLlib run on more platforms?
H2O.ai runs on Web, Cloud. Apache Spark MLlib runs on Linux, macOS, Windows.
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 Apache Spark MLlib is typically brought in for.
What can H2O.ai do that Apache Spark MLlib cannot?
H2O.ai covers AutoML, Distributed computing, Model explainability, Time series forecasting. Apache Spark MLlib covers Classification, Regression, Clustering, Collaborative filtering. Both handle Feature engineering, Hadoop, Linux support, Mac 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
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
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