Microsoft announces Azure Databricks for advanced analytics and enhanced collaboration

Microsoft and Databricks collaboratively announce the availability for Azure Databricks, a fast, easy, and collaborative Apache Spark-based analytics platform optimized for Azure. Azure Databricks is Databricks’ Unified Analytics Platform offered as an integrated service within the Azure cloud platform. The service combines the best of Databricks and Microsoft Azure to help customers accelerate innovation with one-click setup, streamlined workflows, and an interactive workspace that enables collaboration between data scientists, data engineers, and business analysts.

As an Azure service, customers automatically benefit from the native integration with other Azure services such as Power BI, Azure SQL Data Warehouse, and Azure Cosmos DB, as well as from enterprise-grade Azure security, including Azure Active Directory integration, compliance, and enterprise-grade SLAs.

Further with the Microsoft, Databricks collaboration, Azure Databricks and its native integration with other Azure services, Azure is the one-stop destination to easily unlock powerful new analytics, machine learning, and AI scenarios.

Over the past five years, Apache Spark has emerged as the open source standard for advanced analytics, machine learning and AI on Big Data. With a massive community of over 1,000 contributors and the rapid adoption by enterprises, Spark’s popularity has been rising rapidly. Microsoft’s goal with Azure Databricks, designed in collaboration with the founders of Apache Spark, is to help customers accelerate innovation and simplify the process of building Big Data & AI solutions by combining the best of Databricks and Azure.

The Key Basic Design Principles with Azure Databricks include:

• Drive innovation and increase productivity – Azure Databricks interactive notebooks enable data science teams to collaborate using popular languages such as Python, Scala, and SQL and create powerful machine learning models by working on all their data. Native integration with Azure services further simplifies the creation of end-to-end solutions. These capabilities have enabled companies such as renewables.AI to boost the productivity of their data science teams by over 50%.
• Scale without limits– Azure Databricks not only provides an optimized Spark platform which is much faster than open source Apache Spark, but it also simplifies the process of building batch and streaming data pipelines and deploying machine learning models at scale. Customers can now accelerate innovation by analyzing terabytes of data in minutes vs. hours.
• Build on a secure, trusted cloud –  Azure Databricks protects customers data with enterprise-grade SLAs, simplified security and identity & role-based access controls with Azure Active Directory integration.

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