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Machine Learning & Data Science · head to head

Databricks vs Jupyter

Databricks logo

Databricks

Machine Learning & Data Science

Unified analytics platform for data engineering and data science

From
Free
Rated
-
Full reviewWebsite
Jupyter logo

Jupyter

Machine Learning & Data Science

Interactive computing across all programming languages

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; Jupyter notebook format makes version control and collaboration difficult with multiple contributors
  • They diverge on capability: Databricks covers Delta Lake, Jupyter covers Interactive notebooks.

Where they differ

Only the attributes on which Databricks and Jupyter actually diverge.

Attributes where Databricks and Jupyter differ
AttributeDatabricksJupyter
Pricing modelusage-basedUnknown
PlatformsWeb, Aws, Azure, GcpWeb, Cross-platform, Linux, macOS, Windows
Founded20132014

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 Jupyter

  • Interactive notebooks
  • Live code execution
  • Rich visualizations
  • Markdown documentation
  • Multi-language kernels
  • Python
  • R
  • Julia

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

Jupyter

  • 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

Jupyter

  • Notebook format makes version control and collaboration difficult with multiple contributors
  • Performance degrades with large datasets due to loading entire dataset into memory
  • Debugging capabilities limited compared to traditional IDEs
  • No paid support or commercial backing

Pricing, plan by plan

Databricks

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

Jupyter

Free

No published plan breakdown. See the Jupyter review.

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 Jupyter if

  • You need interactive notebooks.
  • You want to start without paying.
  • You work on Web, Cross-platform, Linux, macOS, Windows.
  • You also want live code execution.
Jupyter review

Questions people ask

Is Databricks or Jupyter better?
Neither clearly leads. Databricks starts at Free and Jupyter at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Databricks or Jupyter?
Databricks starts at Free and Jupyter at Free.
Does Databricks or Jupyter run on more platforms?
Databricks runs on Web, Aws, Azure, Gcp. Jupyter runs on Web, Cross-platform, Linux, macOS, 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 Jupyter is typically brought in for.
What can Databricks do that Jupyter cannot?
Databricks covers Delta Lake, Apache Spark, MLflow, Unity Catalog. Jupyter covers Interactive notebooks, Live code execution, Rich visualizations, Markdown documentation. Both handle Web support.

Answered from the vendors’ own pages

Jupyter: Is Jupyter free to use?

Yes, Jupyter is completely free and open-source under the BSD license. There are no paid plans or commercial support requirements.

Source
Jupyter: What programming languages does Jupyter support?

Jupyter supports Python plus over 40 additional programming languages including R, Julia, Scala, and many others through different kernels.

Source
Jupyter: What is JupyterLab?

JupyterLab is the successor to classic Jupyter Notebook, adding a file browser, multiple tabs, terminal access, and an extension ecosystem for enhanced functionality.

Source
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