Databricks: analytics platform, from the original creators of Apache Spark™
Databricks drives innovation by giving you a unified platform for your modern data needs.
Databricks focuses on modern data needs, enabling you to get started quickly without the hassle of managing a complex analytics landscape yourself.
It provides the following functionalities:
- One-click set-up unlocks a fast track towards experimentation and innovation. Databricks offers fully managed Spark clusters in the cloud, provisioned directly from the Azure Portal like any other Azure service, and integrates seamlessly with other Azure services. This integration goes from data services such as Azure SQL DB, Azure CosmosDB and Azure Data Lake to enabling a true CI/CD pipeline with Azure DevOps or creating ready-to-deploy container images for edge devices via Azure Machine Learning Workspace.
- Streamlined workflows offer a production pipeline scheduler to easily schedule a Databricks notebook as a job. This offers a seamless go-live of your data science and engineering efforts: what you write is what you run. Jobs can start and stop a cluster when needed to offer a true pay-as-you-use setup.
- Via the interactive, notebook-style workspace, you enable collaboration between data scientists, data engineers, and business analysts. The workspace allows a one-click interface to assign notebooks to different clusters running different versions of the underlying Spark and Scale/Python runtimes to GPU-enabled clusters.
- Next to the core runtime, Databricks includes MLflow to add DevOps to your machine-learning efforts and Delta to add a governance layer on top of an (Azure) data lake.
- As first-party service on Microsoft Azure, Databricks on Azure offers enterprise-grade Azure security (including out-of-the-box Active Directory integration), compliance and enterprise grade SLAs.
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