Databricks Notebooks: Review, Features and Pricing

The gist

Databricks Notebooks provides a browser editor where users analyze data interactively and inspect results. It suits teams that need shared notebooks, scheduled work and connections to cloud data platforms.

The service is part of Databricks’ broader cloud platform, with separate storage and compute, governance features and data-lake support.

On Android and other platforms

Android appears in the platform list, but Databricks describes notebooks as web-based and excludes mobile browsers from support. Current desktop Chrome, Firefox, Safari and Edge are supported on Windows and macOS.

The platform also lists Windows, macOS, Linux and API access. AWS, Azure and Google Cloud integrations can be deployed through a marketplace or a cloud console.

What it does

Magic commands switch among Python, SQL, Scala and R inside one notebook. Users may execute a single cell, a selected group or the entire notebook interactively, and can arrange for notebooks to run as jobs.

Formatting and autocomplete are built in, while Genie Code can generate, explain and debug code; a Python debugger is also included. A notebook may contain as many as 10,000 cells, with a 6 MB limit per cell and 20 MB for output.

Cells do not execute until their notebook is connected to a cluster. IPYNB/Jupyter is the default notebook format, and source alternatives include .py, .scala, .r and .sql.

Standouts

Multiple coworkers can work in one cell concurrently, view one another’s edits and leave code comments. Five permission levels run from no permissions through manage, with access control available only on Premium or higher.

IPYNB files may retain their outputs and enable enhanced pull-request comparisons through GitHub or GitLab. Partner Connect lets users discover and integrate data, analytics and AI tools from inside Databricks.

The platform includes SQL analytics, streaming ingestion, a governance catalog, automated discovery and column-level, pipeline and report lineage. See related data lakehouse platforms and data lineage tools.

Trade-offs

A cluster must be in place for notebook cells to execute, so notebooks are not standalone local editors. Mobile browsers are unsupported even though Android appears in the platform list.

The Free Edition is serverless-only, quota-limited, offers smaller compute and warehouse sizes, and is intended for personal use. Premium or higher is needed for access control.

Some capabilities sit outside the notebook editor, including broader APIs, model serving, pipeline orchestration and Databricks Apps. The hosted software is not open source, though the platform incorporates separate open-source projects.

Pricing

Databricks offers a no-cost plan alongside a 14-day trial. The Free Edition has no charge, uses serverless resources, carries quotas and is intended for personal use. Trial access lasts 14 days or until credits are depleted, after which billing moves to pay as you go.

Pay-as-you-go pricing is available on request, has no upfront charge and measures usage by the second. Committed Use Contracts are likewise quote-based and apply commitments across multiple clouds.

The listed starting pay-as-you-go rates are $0.07 a month for Artificial Intelligence, $0.15 a month for Data Engineering, $0.22 a month for Data Warehousing and $0.40 a month for Interactive workloads; billing is per DBU.

Verdict

Choose Databricks Notebooks if your work depends on collaborative, cloud-based analysis and you want several notebook languages in one workspace. It is also a fit when scheduled jobs, Git diffs, lineage or cloud integrations matter.

Check the compute requirement and plan limits before committing. The free options are constrained, mobile browser use is unsupported, and costs can move to usage billing after the trial. For a simple personal coding notebook without clusters or cloud services, this platform may be more than you need.