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SQL Server 2008: 1 Trillion Row Query in Seconds

Via Project "Madison"

By Marius Oiaga, Technology News Editor

7th of October 2008, 11:33 GMT

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Microsoft's data platform repertoire is in for a consistent evolution, not only via Gemini and SQL Server codename Kilimanjaro, but also with the project code-named “Madison”. In Microsoft's perspective, “Madison” represents
an integration of the advanced data warehousing capabilities with its data platform. At the Microsoft Business Intelligence Conference on October 6 in Seattle, Ted Kummert, Corporate Vice President, Data and Storage Platform Division, demonstrated how Madison is able to scale to hundreds of terabytes of data.

“Project 'Madison' was announced as the release of SQL Server that will be integrated with the recent DATAllegro acquisition. Project 'Madison' will be capable of handling the most challenging data warehouse workloads which is key since the data warehouse is the hub of any BI solution. At the BI Conference, SQL Server demonstrated how capable this technology really is by using current reporting tools to perform a 1 trillion row query on a 100 TB data warehouse with results returning in seconds,” revealed Anthony Carrabino, Sr. Product Manager, SQL Server.

The evolution of SQL Server toward “Madison” comes as an inherent step of the integration of the technology acquired with data warehouse appliance vendor DATAllegro into Microsoft's data platform. Within a year, the Redmond giant promised that it would deliver the first Community Technology Preview of “Madison”.

“We're moving ahead quickly as you saw with Madison, and taking SQL Server to the highest levels of scale, to the hundreds of terabytes and a solution that will be low-cost, hardware and software together and will be low TCO and will fit together as a part of our BI platform end to end. And that's coming in the first half of calendar year 2010 with the CTP customer technology preview in the next 12 months,” Kummert said.

TAGS:

SQL Server 2008 | Madison | SQL Server | data warehouse | DATAllegro
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