xVelocity in-memory technologies in SQL Server 2012 for 10-100X performance

memory-chips

xVelocity is a family of memory-optimized technologies spanning Analytical, Transactional, Streaming and Caching data. Designed for industry standard hardware, xVelocity is a built-in capability in SQL Server 2012, SQL Server Parallel Data Warehouse, Office Excel 2013 and Windows Azure.

The xVelocity in-memory analytics engine is the next generation of the VertiPaq™ engine that was introduced in SQL Server 2008 R2, with PowerPivot for Excel 2010 and PowerPivot for SharePoint 2010. Vertipaq™ is an in-memory columnstore engine that achieves breakthrough performance for analytic queries by employing techniques such as columnar storage, state-of-the-art compression, in-memory caching and highly parallel data scanning and aggregation algorithms. In SQL Server 2012, the xVelocity in-memory analytics engine has been enhanced to support both self-service BI (PowerPivot) as well as corporate BI (Analysis Services tabular mode) scenarios.

The xVelocity engine has two usage scenarios in the context of Business Intelligence:

  • Information workers can use PowerPivot for Excel to integrate data from a number of sources, cleanse and model the data, enrich the data with business logic, analyze the data and build reports and visualizations. Since PowerPivot uses the xVelocity engine under the covers, information workers are not limited by the restrictions of Excel. They can work with several millions of rows of data and still benefit from split-second response times.

 

  • BI developers and IT professionals can use SQL Server Data Tools to create an Analysis Services Tabular project and build a BI Semantic Model. The model can contain data from a number of sources, business logic expressed in the form of DAX calculations, role-based security and large data volumes that can be managed using partitions in the xVelocity engine. When the model is deployed to an Analysis Services server, information workers can use tools like Excel and Power View to interact with the model and achieve split-second response times from the xVelocity engine.

While other in-memory offerings in the marketplace may have required customers to purchase a separate hardware appliance or expensive add-ons, Microsoft SQL Server 2012 is exposing xVelocity as a core capability directly in its primary database engine. By doing so, you get the benefits of next-generation performance with your current IT hardware and software infrastructure. xVelocity also delivers these dramatic results for both Data Warehousing and Business Intelligence workloads.

  • Data Warehousing: xVelocity memory optimized columnstore index enables you to achieve break-through speed ups for common data warehouse queries. To enable this, your IT staff can simply use SQL Server Management Studio to create the column store. When the query runs, SQL Server will automatically pick the most optimized index and will bring data into or out of memory on demand not requiring you to have a memory capacity that fits your entire dataset. This design gives you the performance gains by fully utilizing the hardware you have today.

 

  • Business Intelligence: xVelocity introduces an in-memory analytics engine within SQL Server Analysis Services delivering faster time to insights. With scan rates of 10s of Billions of rows per second on typical industry hardware, xVelocity gives users the ability to actively interact with an unprecedented amount of data at the speed of thought.

In Analysis Services, the xVelocity engine is enabled when you choose Tabular mode during an Analysis Services installation. You can then author and deploy tabular model projects by using the Analysis Services Tabular Project, Import from PowerPivot, or Import from Server project templates in SQL Server Data Tools. xVelocity is not available with Analysis Services Multidimensional and Data Mining solutions.

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About Zaim Raza

7 Years of professional experience in Business intelligence using SQL Server and Microsoft SharePoint/.net Technologies. Experience in Data warehousing, Data Modeling, Data profiling, Data Integration, Data cleansing, consultations and enterprise reporting. I want to work for organization where I am able to utilize my skills, experience and knowledge to transform the technology into business value.
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