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Disk based database technology has influenced database design since the inception of electronic databases. One of the issues with disk based media is that the physical design of systems tries to speed up processing by reducing disk access, in other words disk input/output (I/O) is a limiting factor which needs to be optimised. In-memory databases have been described as a disruptive technology or disruptive tipping point because it provides a significant improvement in performance and use of system resources.
In-memory databases systems are database management systems where the data is stored entirely in main memory. In memory systems have been shown to be 50,000 times faster than disk based systems. This increase in speed along with a falling cost and non-volatility of computer memory has led to a greater interest in in-memory databases from the mid-2000’s. Preimesberger (2013) coins the term ‘data half-life’ referring to data being more valuable in real time and diminishing in value over time. Therefore speed of processing giving real time insights which can be used immediately is important. In-memory databases therefore allow real-time online analytical processing (OLAP) analysis on data from online transaction processing (OLTP).
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Garcia-Molina H, Salem K (1992) Main memory database systems: an overview. IEEE Trans Knowl Data Eng 4(6):509–516 CrossRef
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Plattner H (2009) A common database approach for OLTP and OLAP using an in-memory column database. In: Proceedings of SIGMOD 09 (special interest group on management of data), Providence, Rhode Island, USA. Available at www.sigmod09.org/images/sigmod1ktp-plattner.pdf. Last accessed 29/06/2013
Preimesberger C (2013) In-memory databases driving big data efficiency: 10 reasons why. e-week, available at http://www.eweek.com/database/slideshows/in-memory-databases-driving-big-data-efficiency-10-reasons-why/, last accessed 14/11/2013.
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SAP (2013b) SAP white paper: SAP HANA ® database for next-generation business applications and real-time analytics explore and analyze vast quantities of data from virtually any source at the speed of thought. Available at http://download.sap.com/download.epd?context=E67AFF9FD4CFC6693FC443EB965A7B4FE599BA88ED6C9F622486D0E5BEB350EB7DAD751393D16A2D916A3C9EA834D1CB2A8138467760590E. Last accessed 29/06/2013
McObject (2013) In-memory database systems—questions and answers. Available at http://www.mcobject.com/in_memory_database. Last accessed 29/06/2013
Oracle Corp (2013) Oracle TimesTen in-memory database and Oracle in-memory database cache. Available at http://www.oracle.com/technetwork/products/timesten/overview/index.html. Last accessed 29/06/2013
SAP (2013a) Consolidate transactional and analytical workloads onto a single, real-time database—with SAP HANA. Available at http://www54.sap.com/pc/tech/in-memory-computing-hana/software/platform/database.html. Last accessed 29/06/2013
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