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Microsoft SQL Server (Structured Query Language) is a proprietary relational database management system developed by Microsoft.As a database server, it is a software product with the primary function of storing and retrieving data as requested by other software applications—which may run either on the same computer or on another computer across a network (including the Internet).
The Core CAL is a special CAL offered by Microsoft through corporate license agreements such as Enterprise, Select or Open Value. The Core CAL is a combination of CALs for Windows Server, Exchange Server, SharePoint Server, System Center Configuration Client Management License, Lync Server, and Forefront Endpoint Subscription License.
Database scalability is the ability of a database to handle changing demands by adding/removing resources. Databases use a host of techniques to cope. [1] According to Marc Brooker: "a system is scalable in the range where marginal cost of additional workload is nearly constant."
Microsoft SQL Server: 524,272 TB (32 767 files × 16 TB max file size) 16ZB per instance 524,272 TB 8,060 bytes / 2 TB 6: 1,024 / 30,000(with sparse columns) 2 GB / Unlimited (using RBS/FILESTREAM object) 2 GB 6: 126 bits 2: 0001 9999 128 Microsoft SQL Server Compact (Embedded Database) 4 GB 4 GB 8,060 bytes 1024 2 GB 4000 154 bits 0001 9999 ...
March 1986: Systemware enters into talks with Microsoft to license Data Server, a database product built to run on UNIX computers. Those talks lead to a product called Ashton-Tate/Microsoft SQL Server 1.0, shipping in May 1989. [6] May 1991: Systemware changes its name to Sybase. [7]
Published surveys on estimation practice suggest that expert estimation is the dominant strategy when estimating software development effort. [ 3 ] Typically, effort estimates are over-optimistic and there is a strong over-confidence in their accuracy.
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Indexing is a technique some storage engines use for improving database performance. The many types of indexes share the common property that they reduce the need to examine every entry when running a query. In large databases, this can reduce query time/cost by orders of magnitude.