Databricks Workspace

Collaboration across the data engineering and data science lifecycle

The Databricks Workspace is a notebook-based collaborative environment capable of running all analytic processes in one place, so you can build data pipelines, train and productionize machine learning models, and share insights to the business all from the same environment.

SQL
Scala
R studio
Python
Java
EXPLORE

Use interactive notebooks to write Spark commands in R, Python, Scala, or SQL and reuse your favorite Python, Java, or Scala libraries.

VISUALIZE

Leverage a wide assortment of point-and-click visualizations. Or use powerful scriptable options like matplotlib, ggplot, and D3.

COLLABORATE

Work on the same notebook in real-time while tracking changes with detailed revision history or GitHub.

PUBLISH

Share insights with your colleagues and customers, or let them run interactive queries with Spark-powered dashboards.

How it works

Databricks Workspace provides a shared and secure interactive workspace for data engineers, data scientists and business stakeholders to collaborate in one place.

Interactive notebooks, experiments, and extended files support allow data scientists teams to organize, share, and manage complex data science projects more effectively throughout the lifecycle. APIs and Job Scheduler allow data engineering teams to quickly automate complex pipelines, while business analysts can directly access results via interactive dashboards.

Benefits

For Data Engineers: Build robust data pipelines, automate and monitor production jobs using Scala, Java and built-in notebooks and APIs.
For Data Scientists: Share, organize and reproduce projects throughout the lifecycle using familiar tools and languages like JupyterLab, Conda, scikit-learn, TensorFlow, R and Python.
For Business Analysts: Discover insights on large data sets using SQL queries, built-in visualizations or dashboards, and connect to popular BI tools like PowerBI and Tableau.

Features

Interactive notebooks

Real-Time Coauthoring
Work on the same notebook in real-time while tracking changes with detailed revision history

Interactive Exploration
Explore data using interactive notebooks with support for multiple programming languages including R, Python, Scala, and SQL.

Visualizations
Visualize insights through a wide assortment of point-and-click visualizations. Or use powerful scriptable options like matplotlib, ggplot, and D3.

Dashboards
Share insights with your colleagues and customers, or let them run interactive queries with Spark-powered dashboards.

Experiments Tracking
Create and track experiments that automatically log data, parameters, and config that went into each run, and trace back each of your runs to the corresponding notebooks.


Production jobs

Jobs Scheduler
Execute jobs for production pipelines on a specific schedule.

Notebook Workflows
Create multi-stage pipelines with the control structures of the source programming language.

Run Notebooks as Jobs
Turn notebooks or JARs into resilient Spark jobs with a click or an API call.

Notifications and Logs
Set up alerts and quickly access audit logs for easy monitoring and troubleshooting.


Data access, security, and management

Data Access
Quickly access available data sets or connect to any data sources, on-premises or in the cloud.

Permissions Management
Quickly manage access to each individual notebook, or a collection of notebooks, and experiments, with one common security model.

Clusters
Quickly create or access on-demand auto-managed clusters to run notebooks and jobs.

Extensibility
Connect to other popular tools (Tableau, Looker, PowerBI, RStudio, SnowFlake etc) allowing data scientists and engineers to use familiar languages and tools.

Integration























Ready to get started?

TRY DATABRICKS FOR FREE