In-memory Databases in Business Information Systems

TLDR: The question of whether in-memory databases as a basic data management technology can sustainably influence the conception and development of business information system or will remain a niche application is discussed.

Abstract: In-memory databases are developed to keep the entire data in main memory. Compared to traditional database systems, read access is now much faster since no I/O access to a hard drive is required. In terms of write access, mechanisms are available which provide data persistence and thus secure transactions. In-memory databases have been available for a while and have proven to be suitable for particular use cases. With increasing storage density of DRAM modules, hardware systems capable of storing very large amounts of data have become affordable. In this context the question arises whether in-memory databases are suitable for business information system applications. Hasso Plattner, who developed the HANA in-memory database, is a trailblazer for this approach. He sees a lot of potential for novel concepts concerning the development of business information systems. One example is to conduct transactions and analytics in parallel and on the same database, i.e. a division into operational database systems and data warehouse systems is no longer necessary (Plattner and Zeier 2011). However, there are also voices against this approach. Larry Ellison described the idea of business information systems based on in-memory database as “wacko,” without actually making a case for his statement (cf. Bube 2010). Stonebraker (2011) sees a future for inmemory databases for business information systems but considers the division of OLTP and OLAP applications as reasonable. Therefore, this discussion deals with the question of whether in-memory databases as a basic data management technology can sustainably influence the conception and development of business information system or will remain a niche application. The contributors were invited to address the following research questions (among others): What are the potentials of in-memory databases for business information systems? What are the consequences for OLTP and OLAP applications? Will there be novel application concepts for business information systems? The following researchers accepted the invitation (in alphabetic order): Dr. Benjamin Fabian and Prof. Dr. Oliver Günther, Humboldt-Universität zu Berlin Prof. Dr. Donald Kossmann, ETH Zürich Dr. Jens Lechtenbörger and Prof. Dr. Gottfried Vossen, Münster University Prof. Dr. Wolfgang Lehner, TU Dresden Prof. Dr. Robert Winter, St. Gallen University Dr. Alexander Zeier with Jens Krüger and Jürgen Müller, Potsdam University Lechtenbörger and Vossen discuss the development and the state of the art of inmemory and column-store technology. In their evaluation they stress the potentials of in-memory technology for energy management (cf. Loos et al. 2011) and Cloud Computing. Zeier et al. argue that the main advantage of modern business information systems is their ability to integrate transactional and analytical processing. They see a general trend towards this mixed processing mode (referred to as OLXP). Inmemory technology supports this integration and will render the architectural separation of transactional systems and management information systems unnecessary in the future. The new database technology also greatly facilitates the integration of simulation and optimization techniques into business information systems. Lehner assumes that the revolutionary development of system technology will have a great impact on future structuring, modeling, and programming techniques for business information systems. One consequence will be a general shift from control-flow-driven to data-flowdriven architectures. It is also likely that the requirement for ubiquitously available data will be abandoned and a “needto-know” principle will establish itself in certain areas. Kossman identifies two phases in which in-memory technology will influence business information systems. The first phase is a simplification phase which is caused by a separation of data and application layers of information systems. In a second phase, however, complexity will increase since the optimization of memory hierarchies, such as the interplay between memory and cache, will also have consequences for application developers. Fabian and Günther stress that inmemory databases have already proven