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Software · head to head

H2O.ai vs Amazon Redshift ML

H2O.ai logo

H2O.ai

Software

AI Cloud for building and deploying AI applications

From
Free
Rated
-
Full reviewWebsite
Amazon Redshift ML logo

Amazon Redshift ML

Software

Create machine learning models using SQL

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; Amazon Redshift ML free tier covers only two CREATE MODEL requests per month for two months, capped at 100,000 cells per request; beyond that training is metered at $20 per million cells for the first 10 million, dropping in tiers to $7 per million cells over 100 million
  • They diverge on capability: H2O.ai covers Distributed computing, Amazon Redshift ML covers SQL-based ML.

Where they differ

Only the attributes on which H2O.ai and Amazon Redshift ML actually diverge.

Attributes where H2O.ai and Amazon Redshift ML differ
AttributeH2O.aiAmazon Redshift ML
Pricing modelfreemiumusage-based
PlatformsWeb, CloudWeb
Founded20112006

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

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

Only in Amazon Redshift ML

  • SQL-based ML
  • SageMaker integration
  • BYOM support
  • In-database predictions
  • Amazon Redshift
  • SageMaker
  • S3
  • Glue

Both cover

  • AutoML
  • 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 Amazon Redshift ML
  • Training and productionising models from R or Python against a shared H2O clusternot Amazon Redshift ML

Amazon Redshift ML

  • Training and running machine learning models directly from SQL inside Amazon Redshiftnot 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

Amazon Redshift ML

  • Free tier covers only two CREATE MODEL requests per month for two months, capped at 100,000 cells per request; beyond that training is metered at $20 per million cells for the first 10 million, dropping in tiers to $7 per million cells over 100 million

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

Amazon Redshift ML

Free
  • Free TrialFree
    • 2-month trial
    • 750 DC2.Large hours
  • On-Demand$0.25/hour
    • Per-node pricing
    • SageMaker training

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.
H2O.ai review

Choose Amazon Redshift ML if

  • You need sql-based ml.
  • You want to start without paying.
  • You also want sagemaker integration.
Amazon Redshift ML review

Questions people ask

Is H2O.ai or Amazon Redshift ML better?
Neither clearly leads. H2O.ai starts at Free and Amazon Redshift ML at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, H2O.ai or Amazon Redshift ML?
H2O.ai starts at Free and Amazon Redshift ML at Free.
Does H2O.ai or Amazon Redshift ML run on more platforms?
H2O.ai runs on Web, Cloud. Amazon Redshift ML runs on 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 Amazon Redshift ML is typically brought in for.
What can H2O.ai do that Amazon Redshift ML cannot?
H2O.ai covers Distributed computing, Feature engineering, Model explainability, Time series forecasting. Amazon Redshift ML covers SQL-based ML, SageMaker integration, BYOM support, In-database predictions. Both handle AutoML, 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
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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