Microsoft has announced the general availability of Azure Databricks, powered by Apache Spark. With the new “fast, easy, and collaborative […] analytics platform”, Microsoft wants to give organisations more power over data to “improve our world.” With Azure Databricks, customers will be able to more easily build big data and AI solutions.
In order to meet this goal, Microsoft developed Azure Databricks with three design principles in mind. The first principle was to enhance user productivity, one way in which Microsoft has achieved this is to provide support for several popular languages including R, Python, Scala, and SQL. The software giant has also included native integration with Azure services to help users get tasks done more efficiently.
The second principle that Microsoft focused on with this product was scalability at affordable prices, it does this without adding further complexities. Additionally, Microsoft claims that Azure Databricks is much faster than Apache Spark thanks to optimisations it has made.
With respect to the third principle, pertaining to security, Microsoft said:
“[We] ensure that we provide our customers with the enterprise security and compliance they have come to expect from Azure. Azure Databricks protects customer data with enterprise-grade SLAs, simplified security and identity, and role-based access controls with Azure Active Directory integration. As a result, organizations can safeguard their data without compromising productivity of their users.”