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Machine Learning · head to head

H2O.ai vs Weaviate

H2O.ai logo

H2O.ai

Machine Learning

AI Cloud for building and deploying AI applications

From
Free
Rated
-
Full reviewWebsite
Weaviate logo

Weaviate

Machine Learning

Open-source vector database

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; Weaviate the free tier caps at 100,000 objects, 1 GB of memory and a single collection
  • They diverge on capability: H2O.ai covers AutoML, Weaviate covers Vector and keyword search.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which H2O.ai and Weaviate actually diverge.

Attributes where H2O.ai and Weaviate differ
AttributeH2O.aiWeaviate
PlatformsWeb, CloudLinux, Mac, Windows, Web
Founded20112019

Identical on both: starting price (Free), pricing model (freemium), 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 H2O.ai

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

Only in Weaviate

  • Vector and keyword search
  • Built-in vectorizers
  • GraphQL API
  • Multi-tenancy
  • Hybrid search
  • OpenAI
  • Hugging Face
  • Cohere

Both cover

  • Linux support
  • Mac support
  • Windows support
  • 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 Weaviate
  • Training and productionising models from R or Python against a shared H2O clusternot Weaviate

Weaviate

  • Running a vector database for semantic and hybrid searchnot H2O.ai
  • Generating and storing embeddings alongside the objects they describenot 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

Weaviate

  • The free tier caps at 100,000 objects, 1 GB of memory and a single collection
  • Billing is per million vector dimensions rather than per record, so wider embeddings cost proportionally more for the same object count
  • Premium is a prepaid contract starting at $400 a month rather than pay as you go
  • Storage rates do not fall consistently with tier, and Premium Dedicated is $0.1505 per GiB against $0.12 on the cheaper Flex plan
  • The Query Agent is metered separately, free to 1,000 requests a month and $30 a month plus overage beyond

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

Weaviate

Free
  • Open SourceFree
    • Full features
    • Self-hosted
  • ServerlessFree
    • Managed service
    • Auto-scaling

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 Weaviate if

  • You need vector and keyword search.
  • You want to start without paying.
  • You work on Linux, Mac, Windows, Web.
  • You also want built-in vectorizers.
Weaviate review

Questions people ask

Is H2O.ai or Weaviate better?
Neither clearly leads. H2O.ai starts at Free and Weaviate at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, H2O.ai or Weaviate?
H2O.ai starts at Free and Weaviate at Free.
Does H2O.ai or Weaviate run on more platforms?
H2O.ai runs on Web, Cloud. Weaviate runs on Linux, Mac, Windows, 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 Weaviate is typically brought in for.
What can H2O.ai do that Weaviate cannot?
H2O.ai covers AutoML, Distributed computing, Feature engineering, Model explainability. Weaviate covers Vector and keyword search, Built-in vectorizers, GraphQL API, Multi-tenancy. Both handle Linux support, Mac support, Windows support, 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
Weaviate: What pricing options does Weaviate offer?

Weaviate provides a free tier with usage-based pricing, plus enterprise options. Visit the pricing page for detailed information on plans.

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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.

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Weaviate: Does Weaviate offer customer support?

Yes, support is included with Weaviate's cloud offerings. Enterprise customers receive first-class support from their global team of experts.

Source
Weaviate: Can I deploy Weaviate on my own infrastructure?

Yes. Weaviate is open source and deployment-agnostic. You can run it in your own cloud environment or use their managed cloud service.

Source
Weaviate: What data security features does Weaviate provide?

Weaviate includes security & governance, RBAC, SOC 2 and HIPAA compliance, along with multi-tenancy and high availability for enterprise requirements.

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Weaviate: How do I get started with Weaviate?

Sign up for their cloud tier, create your first dataset, connect an LLM, and build your AI app. Documentation and quickstart guides are available for Python, Go, TypeScript, and JavaScript.

Source
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