Software · head to head
Weaviate vs Dataiku
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; Dataiku no pricing is published at any tier, and the plans page carries no figures at all
- They diverge on capability: Weaviate covers Vector and keyword search, Dataiku covers Visual data prep.
Where they differ
Only the attributes on which Weaviate and Dataiku actually diverge.
Identical on both: starting price (Free), pricing model (freemium), free tier (Yes), platforms (Linux, Mac, Windows, Web), 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 Dataiku
- Visual data prep
- AutoML
- MLOps
- Collaboration
- Governence
- Python
- R
- Spark
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 Dataiku
- Generating and storing embeddings alongside the objects they describenot Dataiku
Dataiku
- Building and deploying data science and machine learning pipelinesnot Weaviate
- Giving analysts and data scientists a shared visual and code environmentnot 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
Dataiku
- No pricing is published at any tier, and the plans page carries no figures at all
- User, row and compute limits are not stated, so nothing about scale can be assessed before contacting sales
- Access begins with a demo request or a trial rather than a self serve signup
Pricing, plan by plan
Weaviate
Free- Open SourceFree
- Full features
- Self-hosted
- ServerlessFree
- Managed service
- Auto-scaling
Dataiku
Free- Free EditionFree
- Single user
- Core features
- EnterpriseFree
- Full platform
- Collaboration
- MLOps
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 Dataiku if
- You need visual data prep.
- You want to start without paying.
- You work on Linux, Mac, Windows, Web.
- You also want automl.
Questions people ask
- Is Weaviate or Dataiku better?
- Neither clearly leads. Weaviate starts at Free and Dataiku at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Weaviate or Dataiku?
- Weaviate starts at Free and Dataiku at Free.
- Does Weaviate or Dataiku run on more platforms?
- Both run on Linux, Mac, Windows, Web, so platform support will not decide this one for you.
- 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 Dataiku is typically brought in for.
- What can Weaviate do that Dataiku cannot?
- Weaviate covers Vector and keyword search, Built-in vectorizers, GraphQL API, Multi-tenancy. Dataiku covers Visual data prep, AutoML, MLOps, Collaboration. Both handle Linux support, Mac support, Windows support, Web support.