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Machine Learning & Data Science · head to head

Hugging Face vs Databricks

Hugging Face logo

Hugging Face

Machine Learning & Data Science

The AI community building the future

From
Free
Rated
-
Full reviewWebsite
Databricks logo

Databricks

Machine Learning & Data Science

Unified analytics platform for data engineering and data science

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Hugging Face model discovery across 3 million models lacks robust filtering and sorting by quality metrics; Databricks cloud compute is billed separately by the cloud provider on top of Databricks DBU charges
  • They diverge on capability: Hugging Face covers Model hub, Databricks covers Delta Lake.

Where they differ

Only the attributes on which Hugging Face and Databricks actually diverge.

Attributes where Hugging Face and Databricks differ
AttributeHugging FaceDatabricks
Pricing modelUnknownusage-based
PlatformsWeb, APIWeb, Aws, Azure, Gcp
Founded20162013

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Machine Learning & Data Science).

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 Hugging Face

  • Model hub
  • Datasets
  • Spaces
  • Transformers library
  • GitHub
  • Cloud providers
  • MLOps tools
  • Api support

Only in Databricks

  • Delta Lake
  • Apache Spark
  • MLflow
  • Unity Catalog
  • Photon Engine
  • Collaborative Notebooks
  • Auto-scaling
  • AWS

Both cover

  • Web support

What people use each for

The jobs each tool is most often brought in to do.

Hugging Face

  • ai tools managementnot Databricks
  • Workflow automationnot Databricks
  • Reportingnot Databricks

Databricks

  • Running Spark data engineering pipelines on managed clustersnot Hugging Face
  • Building a lakehouse over data in cloud object storagenot Hugging Face
  • Training and serving machine learning models alongside the datanot Hugging Face

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Hugging Face

  • Model discovery across 3 million models lacks robust filtering and sorting by quality metrics
  • Community-driven content means variable model quality and documentation
  • Private models and datasets require Pro subscription
  • Enterprise support and SLAs require custom arrangements

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

Pricing, plan by plan

Hugging Face

Free

No published plan breakdown. See the Hugging Face review.

Databricks

Free
  • Community EditionFree
    • Limited cluster
    • Notebook environment
    • Community support
  • Standard$0.07/DBU
    • Jobs compute
    • SQL compute
    • Standard support

Which should you pick?

Choose Hugging Face if

  • You need model hub.
  • You want to start without paying.
  • You work on Web, API.
  • You also want datasets.
Hugging Face review

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.
Databricks review

Questions people ask

Is Hugging Face or Databricks better?
Neither clearly leads. Hugging Face starts at Free and Databricks at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Hugging Face or Databricks?
Hugging Face starts at Free and Databricks at Free.
Does Hugging Face or Databricks run on more platforms?
Hugging Face runs on Web, API. Databricks runs on Web, Aws, Azure, Gcp.
Can I use Hugging Face for free?
Both have a free tier, so you can try either at no cost before committing.
What is Hugging Face best used for?
Hugging Face is most often used for ai tools management, workflow automation, reporting. Of those, ai tools management and workflow automation are not what Databricks is typically brought in for.
What can Hugging Face do that Databricks cannot?
Hugging Face covers Model hub, Datasets, Spaces, Transformers library. Databricks covers Delta Lake, Apache Spark, MLflow, Unity Catalog. Both handle Web support.

Answered from the vendors’ own pages

Hugging Face: Is Hugging Face free to use?

Yes. Hugging Face allows users to host and collaborate on unlimited public models, datasets, and applications at no cost. Models can be accessed and used freely from the Hub.

Source
Hugging Face: How many models are available on Hugging Face?

Hugging Face Hub currently hosts nearly 3 million machine learning models across various tasks including text generation, image processing, and video generation.

Source
Hugging Face: What is the Hugging Face Inference API?

Hugging Face provides access to 45,000+ models from leading AI providers through a single unified API with no service fees, simplifying access to diverse models.

Source
Hugging Face: What content types does Hugging Face support?

Hugging Face supports text, image, video, audio, and 3D content models, allowing collaboration across multiple modalities and use cases.

Source
Hugging Face: What is the transformers library?

Transformers is a Hugging Face library built for natural language processing applications, providing pre-built models and utilities for NLP tasks.

Source
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