Softwr

Machine Learning & Data Science · head to head

Databricks vs DVC

Databricks logo

Databricks

Machine Learning & Data Science

Unified analytics platform for data engineering and data science

From
Free
Rated
-
Full reviewWebsite
DVC logo

DVC

Machine Learning & Data Science

Data version control for machine learning projects

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Databricks cloud compute is billed separately by the cloud provider on top of Databricks DBU charges; DVC dVC is Apache 2.0 licensed open source with no enterprise tier or paid support offering documented in the project itself; teams needing SLA-backed support get nothing from the DVC project directly.
  • They diverge on capability: Databricks covers Delta Lake, DVC covers Data versioning.

Where they differ

Only the attributes on which Databricks and DVC actually diverge.

Attributes where Databricks and DVC differ
AttributeDatabricksDVC
Pricing modelusage-basedopen-source
PlatformsWeb, Aws, Azure, GcpLinux, Mac, Windows
Founded20132018

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 Databricks

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

Only in DVC

  • Data versioning
  • Pipeline management
  • Experiment tracking
  • Remote storage
  • Git integration
  • Git
  • S3
  • Azure Blob

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 DVC
  • Building a lakehouse over data in cloud object storagenot DVC
  • Training and serving machine learning models alongside the datanot DVC

DVC

  • Machine learningnot Databricks
  • Data analysisnot Databricks
  • Model trainingnot Databricks
  • Predictive analyticsnot 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

DVC

  • DVC is Apache 2.0 licensed open source with no enterprise tier or paid support offering documented in the project itself; teams needing SLA-backed support get nothing from the DVC project directly.

Pricing, plan by plan

Databricks

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

DVC

Free
  • Open SourceFree
    • Data versioning
    • Pipeline management
    • Experiment tracking
  • DVC StudioFree
    • Web UI
    • Team collaboration
    • Visualizations

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.
Databricks review

Choose DVC if

  • You need data versioning.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want pipeline management.
DVC review

Questions people ask

Is Databricks or DVC better?
Neither clearly leads. Databricks starts at Free and DVC at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Databricks or DVC?
Databricks starts at Free and DVC at Free.
Does Databricks or DVC run on more platforms?
Databricks runs on Web, Aws, Azure, Gcp. DVC runs on Linux, Mac, Windows.
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 DVC is typically brought in for.
What can Databricks do that DVC cannot?
Databricks covers Delta Lake, Apache Spark, MLflow, Unity Catalog. DVC covers Data versioning, Pipeline management, Experiment tracking, Remote storage.
ShareXLinkedInRedditWhatsAppEmail

Related pages

More on Databricks

More on DVC

Keep looking

Other head to heads