Software · head to head
Weaviate vs H2O.ai
The short version
- Each has a real cost: Weaviate the free tier caps at 100,000 objects, 1 GB of memory and a single collection; 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: Weaviate covers Vector and keyword search, H2O.ai covers AutoML.
Where they differ
Only the attributes on which Weaviate and H2O.ai actually diverge.
Identical on both: starting price (Free), pricing model (freemium), 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 Weaviate
- Vector and keyword search
- Built-in vectorizers
- GraphQL API
- Multi-tenancy
- Hybrid search
- OpenAI
- Hugging Face
- Cohere
Only in H2O.ai
- AutoML
- Distributed computing
- Feature engineering
- Model explainability
- Time series forecasting
- Spark
- Hadoop
- Python
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.
Weaviate
- Running a vector database for semantic and hybrid searchnot H2O.ai
- Generating and storing embeddings alongside the objects they describenot H2O.ai
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
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
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
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
Weaviate
Free- Open SourceFree
- Full features
- Self-hosted
- ServerlessFree
- Managed service
- Auto-scaling
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 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.
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 Weaviate or H2O.ai better?
- Neither clearly leads. Weaviate 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, Weaviate or H2O.ai?
- Weaviate starts at Free and H2O.ai at Free.
- Does Weaviate or H2O.ai run on more platforms?
- Weaviate runs on Linux, Mac, Windows, Web. H2O.ai runs on Web, Cloud.
- Can I use Weaviate for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Weaviate best used for?
- Weaviate is most often used for running a vector database for semantic and hybrid search, generating and storing embeddings alongside the objects they describe. Of those, running a vector database for semantic and hybrid search and generating and storing embeddings alongside the objects they describe are not what H2O.ai is typically brought in for.
- What can Weaviate do that H2O.ai cannot?
- Weaviate covers Vector and keyword search, Built-in vectorizers, GraphQL API, Multi-tenancy. H2O.ai covers AutoML, Distributed computing, Feature engineering, Model explainability. 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.
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.
Source