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In SQL Server versions 6.5 and earlier, database administrators (DBAs) used SQL Server Transfer Manager and Bulk Copy Program, included with SQL Server, to transfer data. These tools had significant shortcomings, and many [ quantify ] DBAs used third-party tools such as Pervasive Data Integrator to transfer data more flexibly and easily.
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The vague adjectives of very and large allow for a broad and subjective interpretation, but attempts at defining a metric and threshold have been made. Early metrics were the size of the database in a canonical form via database normalization or the time for a full database operation like a backup.
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).
Microsoft SQL Server Integration Services (SSIS) is a component of the Microsoft SQL Server database software that can be used to perform a broad range of data migration tasks. SSIS is a platform for data integration and workflow applications. It features a data warehousing tool used for data extraction, transformation, and loading (ETL).
An operational data store (ODS) is used for operational reporting and as a source of data for the enterprise data warehouse (EDW). It is a complementary element to an EDW in a decision support environment, and is used for operational reporting, controls, and decision making, as opposed to the EDW, which is used for tactical and strategic decision support.
Snowflake Cloud Data Warehouse: Proprietary solidDB: Proprietary SurrealDB: Proprietary SQL Anywhere (formerly known as Sybase Adaptive Server Anywhere and Watcom SQL) Proprietary SQL Azure (Cloud SQL Server) Proprietary SQLBase: Proprietary SQLite: Public Domain SQream DB: Proprietary SAP Advantage Database Server (formerly known as Sybase ...
A common data warehouse example involves sales as the measure, with customer and product as dimensions. In each sale a customer buys a product. The data can be sliced by removing all customers except for a group under study, and then diced by grouping by product. A dimensional data element is similar to a categorical variable in statistics.