Microsoft re-ignites the 2016 love for Apache Spark by optimising it for Azure.
Microsoft is helping its customers to get to grips with their data on its cloud platform with the addition of Databricks.
The Apache Spark based data analytics platform, will appear as Azure Databricks in the Azure Portal, as part of the partnership between the two companies.
The link-up is said to address the customer demand for Apache Spark on Azure.
“Our alliance with Microsoft is a major milestone for the growth of Databricks’ Unified Analytics Platform,” said Ali Ghodsi, cofounder and CEO at Databricks. “There’s a large base of Microsoft Azure customers looking for a high-performance analytics platform based on Spark – and Databricks is already the leading Cloud platform for Spark. These organizations will be able to simplify Big Data and AI with Azure Databricks.”
The Azure Databricks tool will use the core functionality of Databricks’ Unified Analytics Platform, which includes things like a collaborative work space for Data Science and Data Engineering teams.
there is also a single, unified engine for all types of analytics – the usual suspects of batch, ad hoc, machine learning, and deep learning, streaming, graph, and a serverless cloud infrastructure that is fully managed.
The preview, which was announced at Microsoft Connect 2017, came alongside a number of other announcements from the company.
Microsoft also announced a Cassandra API preview for Azure Cosmos DB that is said to expand on the multi-model capabilities of Azure Cosmos DB so that Cassandra can be offered as-a-Service over turnkey global distribution.
There’s also a new cloud service for developers in the form of Visual Studio App Centre GA. The idea of the service is to ship higher quality applications more frequently.
Azure DevOps Projects will give developers the ability to configure a full DevOps pipeline and connect to Azure in 5 minutes – according to the company.
Azure IoT Edge is now available in preview, this is the company’s play to enable AI, advanced analytics, and machine learning at the edge, or IoT devices.
The final announcement is the preview of Azure SQL Database Machine Learning services. There’s now support for R models inside SQL Database, meaning that data scientists will be able to train models in Azure Machine Learning and then deploy them directly to the SQL Database on the cloud platform.