Microsoft's Project Gemini Compelling and Complementary to Tableau
At the Microsoft BI Conference yesterday, Microsoft announced new technologies they are working on, in particular a set of technologies called Project Gemini. Project Gemini is a code name for Microsoft's new managed self-service analysis capabilities that will be added to their Business Intelligence software suite. In short, our take on Project Gemini is this is compelling new technology and a great initiative by Microsoft in making data available for interactive discovery and analytics.
Tableau has always believed that a fast data engine enhances the analytic experience. We have designed the Tableau products to leverage the power of the database engine to provide a live, always-current data analysis solution. There are a number of ways to get fast analytic queries. Dataupia, Netezza, and Teradata are all recent partners Tableau has extended our products to work with. These are databases specifically designed and optimized for high performance for analytic queries with large volumes of data. Microsoft has always been a part of our network with SQL Server and the high performance Microsoft Analysis Services (MSAS). Now Project Gemini promises to provide even greater performance to Analysis Services deployments, with even larger data volumes. Microsoft pre-briefed us last week and we applaud this project heartily.
With Project Gemini, Microsoft is building an in-memory data store as an option for Analysis Services. Once the data is loaded into the Microsoft in-memory data engine, a key aspect of the Project Gemini announcement is the publishing of this data to a SharePoint Server. By publishing the data to a server environment which includes SharePoint, Excel Server, and Analysis Services, the data becomes instantly available to all tools that can access the Analysis Services engine.
The new in-memory engine is in essence becoming an alternate storage mechanism for Analysis Services. Today, Analysis Services supports a MOLAP data engine (pre-built cubes of data) and a ROLAP data engine (data stored in relational format that is modeled to look like a cube). With Project Gemini, Analysis Services now gets a lightning fast, highly scalable in-memory data engine. And this will still look just like regular Analysis Services to any tool that uses MDX to connect to Analysis Services.
We believe there is no better tool to connect to Analysis Services than Tableau. We will simply inherit all the performance gains of the in-memory engine automatically with our support for MSAS today.
As a certified Microsoft Gold Partner, Tableau is excited about the new technology Microsoft is building. We’re looking forward to getting our hands on alpha & beta copies of it so we can start validating and further optimizing our support for the Microsoft data engine.