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In-database processing, also known as in-database analytics, is a technology that concentrates of fusing database warehouses with analytical systems. Normally, a database warehouse must export the information into an analytical program to run extensive computations on the data. With in-database processing, all of the computations are done from a single program. This saves time, because the time needed for exporting is removed, and it speeds up the database to produce real-time results. Many database vendors that make database programs for large businesses offer this as a feature.
Database programs that do not include in-database processing separate database warehouses from analytical programs. A database warehouse is a type of database meant for storing and reporting data. These warehouses include a layer for raw data from developers, a layer for data from users and a third layer where users input data. A database warehouse can typically perform some computations, but only small ones.
Analytical programs are able to perform these larger computations, but only if the database warehouse exports the data. For small databases, moving the data between the two programs might not impede performance, but large businesses might have to wait hours before computations are finished. Moving data might also lead to inaccuracies if the administrator forgets to move a certain portion of the database.
In-database processing fixes these potential errors and problems. Instead of moving data, all of the processing and computations are done from the database warehouse itself. The performance benefits include a large speed boost, enough to make the database provide real-time results, and near removal of potential inaccuracies. Many large databases, such as those used for fraud detection and stock market databases, use this technology.
One of the main features of in-database processing is predictive analytics. This is when an analytical program takes database information and attempts to predict a trend. This is not specific to in-database processing, but it is able to quickly make such a prediction, which allows a business to do better than those with slower systems.
This type of technology typically is unneeded by small businesses, so most vendors lean this feature toward large business database programs. In-database processing usually comes standard for these large business solutions because it is very difficult to get results and information from the database without this processing feature. These businesses also have more data than they know, and this powerful processing system is needed to go through all the data and use it for the business’ benefit.
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