Azure Databricks is optimized for Azure and tightly integrated with Azure Data Lake Storage, Azure Data Factory, Azure Machine Learning, Azure Synapse Analytics, Power BI and other Azure services to store all of your data on a simple, open lakehouse and unify all of your analytics and AI workloads.


Unify your data, analytics, and AI
on one common platform for all data use cases


Unify your data ecosystem
with open source, standards, and formats


Unify your data teams
to collaborate across the entire data and AI workflow

Azure Databricks 3-part training series

Azure Databricks 3-part training series

Get started building a data lakehouse with Azure Databricks and begin to understand its capabilities and how data analysts can leverage SQL to query data in the lakehouse. You will learn how to train a machine learning (ML) model using customer product usage data with Azure Databricks.
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Why Azure Databricks?

50x Performance for Apache SparkTMWorkloads

Deploy auto-scaling compute clusters with highly-optimized Spark that perform up to 50x faster. Learn more.

Millions of server hours each day

Azure Databricks is trusted by thousands of customers who run millions of server hours each day across more than 34 Azure regions. Learn more.

Ease of use

Start with a single click in the Azure Portal, natively integrate with Azure security and data services, and boost productivity by up to 25% with collaborative data engineering and data science. Learn more.

Industry use cases

Azure Databricks event

Join an Azure Databricks event

Databricks, Microsoft and our partners are excited to host these events dedicated to Azure Databricks. Please join us at an event near you to learn more about the fastest-growing Data + AI service on Azure! The agenda and format will vary, please see the specific event page for details.

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Optimized for Azure

Seamlessly integrate to Azure data stores and services with specialized connectors for fast data access and simplified management across your environment. This makes it easy to setup security controls, manage environments, and process all your Azure data.

Featured Integrations

Single Sign-On with Azure Active Directory is the best way to sign in to Azure Databricks. Azure Databricks also supports automated user provisioning with Azure AD to create new users, give them the proper level of access, and remove users to deprovision access.

The Azure Databricks native connector to ADLS supports multiple methods of access to your data lake.  Simplify data access security by using the same Azure AD identity that you use to log into Azure Databricks with Azure Active Directory Credential Passthrough.  Your data access is controlled via the ADLS roles and Access Control Lists you have already set up.

Seamlessly run Azure Databricks jobs using Azure Data Factory and leverage 90+ built-in data source connectors to ingest all of your data sources into a single data lake. ADF provides built-in workflow control, data transformation, pipeline scheduling, data integration, and many more capabilities to help you create reliable data pipelines.

Azure Databricks integrates with Microsoft Azure Machine Learning (AML) via MLflow to centrally track ML experiments and deploy models to Azure containers for on-demand inferencing.  Azure Databricks can also use AML’s automated machine learning capabilities through the AML SDK.

One of the key features customers look for when adopting a Lakehouse strategy is the ability to efficiently and securely consume data directly from the data lake with BI tools. This typically reduces the additional latency, compute, and storage costs associated with the traditional flow of copying data already stored in a data lake to a data warehouse for BI consumption. The Azure Databricks connector in Power BI makes for a more secure, more interactive data visualization experience for data stored in your data lake.

Azure Databricks connects with Azure DevOps to help enable Continuous Integration and Continuous Deployment (CI/CD). Configure Azure DevOps as your Git provider and take advantage of the integrated version control features.

The default deployment of Azure Databricks is a fully managed service on Azure that includes a virtual network (VNet).  Azure Databricks also supports deployment in your own virtual network (sometimes called VNet injection) that enables full control of network security rules.

Get insights from live streaming data by connecting Azure Event Hubs to Azure Databricks, then process messages as they arrive. With Event Hubs and Azure Databricks, stream millions of events per second from any IoT device, or logs from website clickstreams, and process it in near-real time.

Manage your secrets such as keys and passwords with integration to Azure Key Vault. By default, all Azure Databricks notebooks and results are encrypted at rest with a different encryption key. If you want to own and manage the key used for encrypting your notebooks and results yourself, you can bring your own key (BYOK).