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Users query the data loaded into the system's memory, thereby avoiding slower database access and performance [[Bottleneck (software)|bottlenecks]]. This differs from [[caching (computing)|caching]], a very widely used method to speed up query performance, in that caches are subsets of very specific pre-defined organized data. With in-memory tools, data available for analysis can be as large as a [[data mart]] or small data warehouse which is entirely in memory. This can be accessed quickly by multiple concurrent users or applications at a detailed level and offers the potential for enhanced analytics and for scaling and increasing the speed of an application. Theoretically, the improvement in data access speed is 10,000 to 1,000,000 times compared to the disk.{{citation needed|date=January 2016}} It also minimizes the need for performance tuning by IT staff and provides faster service for end users.
=== Advantages of in-memory processing technology ===
Certain developments in computer technology and business needs have tended to increase the relative advantages of in-memory technology.<ref>{{cite web|title=In_memory Analytics|url=http://www.yellowfinbi.com/Document.i4?DocumentId=104879|publisher=yellowfin|page=6}}</ref>
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