Microsoft’s Azure Synapse Analytics bridges the gap between data lakes and warehouses

At its annual Ignite conference in Orlando, Fla., Microsoft today announced a major new Azure service for enterprises: Azure Synapse Analytics, which Microsoft describes as “the next evolution of Azure SQL Data Warehouse.” Like SQL Data Warehouse, it aims to bridge the gap between data warehouses and data lakes, which are often completely separate. Synapse also taps into a wide variety of other Microsoft services, including Power BI and Azure Machine Learning, as well as a partner ecosystem that includes Databricks, Informatica, Accenture, Panoply, Talend, Attunity, Pragmatic Works and Adatis. It’s also integrated with Apache Spark.

The idea here is that Synapse allows anybody working with data in those disparate places to manage and analyze it from within a single service. It can be used to analyze relational and unstructured data, using standard SQL.

Microsoft also highlights Synapse’s integration with Power BI, its easy to use business intelligence and reporting tool, as well as Azure Machine Learning for building models.

With the Azure Synapse studio, the service provides data professionals with a single workspace for prepping and managing their data, as well as for their big data and AI tasks. There’s also a code-free environment for managing data pipelines.

As Microsoft stresses, businesses that want to adopt Synapse can continue to use their existing workloads in production with Synapse and automatically get all of the benefits of the service. “Businesses can put their data to work much more quickly, productively, and securely, pulling together insights from all data sources, data warehouses, and big data analytics systems,” writes Microsoft CVP of Azure Data, Rohan Kumar.

In a demo at Ignite, Kumar also benchmarked Synapse against Google’s BigQuery. Synapse ran the same query over a petabyte of data in 75% less time. He also noted that Synapse can handle thousands of concurrent users — unlike some of Microsoft’s competitors.