A collection of data and filing the same in an organized manner is known as a database. When a software application interacts with databases, other applications and the user, to collect and analyze data, it is known as a database management system or DBMS. DBMS serves several purposes such as administration of databases, creation of data and updating of data among others. In memory database (IMDB) is a form of DBMS which utilizes the main memory of the device, for data storage. In memory database is also known as main memory database system (MMDB) or memory resistant database. When compared with disk optimized databases, the in memory database system functions much faster since it memory access is much faster than disk access. Most database management systems, such as Oracle, MySQL and Microsoft SQL Server utilize the mechanism of disk storage whereas in memory database systems, such as Oracle Coherence and Starcounter among others utilize the mechanism of memory access. In memory databases generally utilize volatile memory. But the introduction of non volatile memory modules has enabled the storage of data even in the event of power failure. Customized versions of in memory databases can offer several advantages. Some such advantages are the ability to accumulate and store large quantities of multidisciplinary data in a relational format, without having to wait for the slower batch processing and ability to predict events of find anomalies in data, by processing historical data and real-time data simultaneously.
The market for in memory database is primarily being driven by the growing demand for real-time monitoring of data and analytical data processing from most industry verticals. Industries such as e-commerce or retail has been more focused on gathering data on consumers for better understanding and predicting the purchasing behavior of the consumers. In line memory database strongly aids the organizations in performing the same and hence has been seeing good growth rate for the past few years. Additionally, the growth of internet-of-things connected devices has been promoting the growth of in memory databases market, since most of the infrastructure of IoT applications are being supported by these databases. Furthermore, the growing demand for advanced risk management solutions by various organizations has also been positively impacting the growth of in memory databases market. Considering the impact of all the factors mentioned above, the market for in memory databases can be expected to grow at a fast pace, during the forecast period from 2016 – 2024. The ongoing shift from in memory databases being a response time improver of analytical data processing to an enabler of online analytical processing (OLAP) / online transaction processing (OLTP) infrastructure is expected to offer unique opportunities for the in memory database market to grow.
On the basis of IT architecture, the in memory database market has been segmented into Enterprise resource planning (ERP) on in memory database, OLAP and OLTP integrated in memory database and others. The global in memory database market, by end-use industry, has been segmented into six types. They are advertising, retail & e-Commerce, banking financial services and insurance (BFSI), government & public sector, power generation & utilities and others. In memory databases for retail & e-commerce sector allows for optimizing customer interactions, while in the sector of BFSI, in memory database allows real-time analysis of data to aid analysts, insurers and asset managers among others to better manage customers. The global in memory database market has again being segmented into five regions: North America, Europe, Asia Pacific (APAC), South America and Middle-East & Africa (MEA).
The major companies of the in memory database market globally are Microsoft Corporation (U.S.), Oracle Corporation (U.S.), International Business Machines Corporation (U.S.), Altibase Corporation (U.S.), and SAP SE (Germany), among various other companies.
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