Software · head to head
DataRobot vs Weaviate

DataRobot
Software
Enterprise AI platform for automated machine learning
- From
- On request
- Rated
- -
The short version
- Only Weaviate has a free tier, so it costs nothing to try first.
- Each has a real cost: DataRobot model transparency is limited, often resembling a black box with limited explainability; Weaviate the free tier caps at 100,000 objects, 1 GB of memory and a single collection
- They diverge on capability: DataRobot covers Automated ML, Weaviate covers Vector and keyword search.
Where they differ
Only the attributes on which DataRobot and Weaviate actually diverge.
Identical on both: 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 DataRobot
- Automated ML
- Model deployment
- Time series
- MLOps
- Model monitoring
- Snowflake
- Databricks
- AWS
Only in Weaviate
- Vector and keyword search
- Built-in vectorizers
- GraphQL API
- Multi-tenancy
- Hybrid search
- OpenAI
- Hugging Face
- Cohere
Both cover
- Web support
What people use each for
The jobs each tool is most often brought in to do.
DataRobot
- Machine learningnot Weaviate
- Data analysisnot Weaviate
- Model trainingnot Weaviate
- Predictive analyticsnot Weaviate
Weaviate
- Running a vector database for semantic and hybrid searchnot DataRobot
- Generating and storing embeddings alongside the objects they describenot DataRobot
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
DataRobot
- Model transparency is limited, often resembling a black box with limited explainability
- Requires integration with separate data manipulation tools for complex data transformation
- Lacks native Python and R code customization for proprietary algorithms
- Dependence on cloud connectivity means offline capabilities are not available
- Uploading sensitive data to third-party servers raises data privacy and security concerns
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
DataRobot
On request- TrialFree
- Limited access
- Basic features
- EnterpriseFree
- Full platform
- AutoML
- MLOps
Weaviate
Free- Open SourceFree
- Full features
- Self-hosted
- ServerlessFree
- Managed service
- Auto-scaling
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.
Questions people ask
- Is DataRobot or Weaviate better?
- Neither clearly leads. DataRobot starts at On request and Weaviate at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, DataRobot or Weaviate?
- Weaviate has a free tier; the other does not. Paid plans start at On request for DataRobot and Free for Weaviate.
- Does DataRobot or Weaviate run on more platforms?
- DataRobot runs on Web. Weaviate runs on Linux, Mac, Windows, Web.
- Can I use Weaviate for free?
- Yes. Weaviate has a free tier, so you can try it without paying. DataRobot starts at On request.
- What is DataRobot best used for?
- DataRobot is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what Weaviate is typically brought in for.
- What can DataRobot do that Weaviate cannot?
- DataRobot covers Automated ML, Model deployment, Time series, MLOps. Weaviate covers Vector and keyword search, Built-in vectorizers, GraphQL API, Multi-tenancy. Both handle Web support.
Answered from the vendors’ own pages
DataRobot: Does DataRobot require data science expertise?
DataRobot automates much of the ML pipeline including data preparation, feature engineering, and model selection, making it more accessible to non-experts, though it is still an enterprise platform.
SourceDataRobot: What does DataRobot cost?
DataRobot uses custom enterprise pricing with typical starting costs around $2,500 per month for smaller organizations. For 10 users, monthly costs range from $15,000 to $20,000. Implementation and professional services are 20-40% of first-year contract value.
SourceDataRobot: Does DataRobot support generative AI?
Yes, DataRobot offers generative AI capabilities with API-first integrations for LLMs, vector databases, and embedding models.
SourceDataRobot: Can DataRobot handle unstructured data?
Yes, DataRobot supports machine learning on both structured and unstructured data, including deep learning, NLP, and image analysis.
SourceRelated pages
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