Machine Learning · head to head
Databricks vs H2O.ai

Databricks
Machine Learning
Unified analytics platform for data engineering and data science
- From
- Free
- Rated
- -

H2O.ai
Machine Learning
AI Cloud for building and deploying AI applications
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Databricks cloud compute is billed separately by the cloud provider on top of Databricks DBU 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
- They diverge on capability: Databricks covers Delta Lake, H2O.ai covers AutoML.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Databricks and H2O.ai actually diverge.
| Attribute | Databricks | H2O.ai |
|---|---|---|
| Pricing model | usage-based | freemium |
| Platforms | Web, Aws, Azure, Gcp | Web, Cloud |
| Founded | 2013 | 2011 |
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Machine Learning).
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 Databricks
- Delta Lake
- Apache Spark
- MLflow
- Unity Catalog
- Photon Engine
- Collaborative Notebooks
- Auto-scaling
- AWS
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.
Databricks
- Running Spark data engineering pipelines on managed clustersnot H2O.ai
- Building a lakehouse over data in cloud object storagenot H2O.ai
- Training and serving machine learning models alongside the datanot H2O.ai
H2O.ai
- Distributed in-memory machine learning over large datasetsnot Databricks
- Training and productionising models from R or Python against a shared H2O clusternot Databricks
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Databricks
- Cloud compute is billed separately by the cloud provider on top of Databricks DBU charges
- The free trial lasts 14 days
- Discounts require a Committed Use Contract, with larger commitments needed for larger discounts
- Azure Databricks pricing is set by Microsoft rather than by Databricks
- Security and compliance capabilities are sold as separate platform add ons rather than included in the base rate
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
Databricks
Free- Community EditionFree
- Limited cluster
- Notebook environment
- Community support
- Standard$0.07/DBU
- Jobs compute
- SQL compute
- Standard support
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 Databricks if
- You need delta lake.
- You want to start without paying.
- You work on Web, Aws, Azure, Gcp.
- You also want apache spark.
Choose H2O.ai if
- You need automl.
- You want to start without paying.
- You work on Web, Cloud.
- You also want distributed computing.
Questions people ask
- Is Databricks or H2O.ai better?
- Neither clearly leads. Databricks 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, Databricks or H2O.ai?
- Databricks starts at Free and H2O.ai at Free.
- Does Databricks or H2O.ai run on more platforms?
- Databricks runs on Web, Aws, Azure, Gcp. H2O.ai runs on Web, Cloud.
- Can I use Databricks for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Databricks best used for?
- Databricks is most often used for running spark data engineering pipelines on managed clusters, building a lakehouse over data in cloud object storage, training and serving machine learning models alongside the data. Of those, running spark data engineering pipelines on managed clusters and building a lakehouse over data in cloud object storage are not what H2O.ai is typically brought in for.
- What can Databricks do that H2O.ai cannot?
- Databricks covers Delta Lake, Apache Spark, MLflow, Unity Catalog. H2O.ai covers AutoML, Distributed computing, Feature engineering, Model explainability. Both handle Web support.
Answered from the vendors’ own pages
Databricks: How is Databricks priced?
Databricks bills pay as you go with no up front cost, charging per second for the products used. Consumption is measured in Databricks Units, a normalised unit of processing power on the platform.
SourceH2O.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.
SourceDatabricks: Does Databricks publish a per DBU price?
Not on its main pricing page. Rates vary by product and instance type, and Databricks directs buyers to individual product pricing pages and a calculator rather than listing a single figure.
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.
SourceDatabricks: Does the Databricks price include cloud costs?
No. Databricks states that if you configure it to work with your own cloud account, your cloud provider still charges you separately for the underlying resources.
SourceDatabricks: Can I get a discount on Databricks?
Databricks offers Committed Use Contracts, where larger usage commitments earn greater benefits, including options to use commitments flexibly across multiple clouds.
SourceRelated pages
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