Software · head to head
Databricks vs Weaviate
Databricks
Software
Unified analytics platform for data engineering and data science
- 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; Weaviate the free tier caps at 100,000 objects, 1 GB of memory and a single collection
- They diverge on capability: Databricks covers Delta Lake, Weaviate covers Vector and keyword search.
Where they differ
Only the attributes on which Databricks and Weaviate actually diverge.
| Attribute | Databricks | Weaviate |
|---|---|---|
| Pricing model | usage-based | freemium |
| Platforms | Web, Aws, Azure, Gcp | Linux, Mac, Windows, Web |
| Founded | 2013 | 2019 |
Identical on both: starting price (Free), 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 Databricks
- Delta Lake
- Apache Spark
- MLflow
- Unity Catalog
- Photon Engine
- Collaborative Notebooks
- Auto-scaling
- 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.
Databricks
- Running Spark data engineering pipelines on managed clustersnot Weaviate
- Building a lakehouse over data in cloud object storagenot Weaviate
- Training and serving machine learning models alongside the datanot Weaviate
Weaviate
- Running a vector database for semantic and hybrid searchnot Databricks
- Generating and storing embeddings alongside the objects they describenot 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
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
Databricks
Free- Community EditionFree
- Limited cluster
- Notebook environment
- Community support
- Standard$0.07/DBU
- Jobs compute
- SQL compute
- Standard support
Weaviate
Free- Open SourceFree
- Full features
- Self-hosted
- ServerlessFree
- Managed service
- Auto-scaling
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 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 Databricks or Weaviate better?
- Neither clearly leads. Databricks 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, Databricks or Weaviate?
- Databricks starts at Free and Weaviate at Free.
- Does Databricks or Weaviate run on more platforms?
- Databricks runs on Web, Aws, Azure, Gcp. Weaviate runs on Linux, Mac, Windows, Web.
- 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 Weaviate is typically brought in for.
- What can Databricks do that Weaviate cannot?
- Databricks covers Delta Lake, Apache Spark, MLflow, Unity Catalog. Weaviate covers Vector and keyword search, Built-in vectorizers, GraphQL API, Multi-tenancy. Both handle Web support.