Joint Colloquium Distinguished Lecture Series
Wednesday, March 10, 2010
When SQL and the relational data model were introduced 25 years ago as a general data management concept, enterprise software migrated quickly to this new technology. It is fair to say that SQL and the various implementations of RDBMSs became the backbone of enterprise systems. In those days, we believed that business planning, transaction processing and analytics should reside in one single system. Despite the incredible improvements in computer hardware, high-speed networks, display devices and the associated software, speed and flexibility remained an issue.
The nature of RDBMSs, being organized along rows, prohibited us from providing instant analytical insight and finally led to the introduction of so-called data warehouses. This talk will question some of the fundamentals of the separation between OLAP and OLTP. Based on the analysis of real customer environments and experience with some prototypical implementations, a new proposal for an enterprise data management concept will be presented.
In our proposal, the participants in enterprise applications, such as customers, orders, accounting documents, products, employees etc. will be modeled as objects and also stored and maintained as such. Despite that, the vast majority of business functions will operate on an in-memory representation of their objects. Using the relational algebra and a column-based data storage will allow us to revolutionize transactional applications while providing an optimal platform for analytical data processing. The unification of OLTP and OLAP workloads on a shared architecture and the reintegration of planning activities promise significant gains in application development while simplifying enterprise systems dramatically.
The latest trends in computer technology – e.g. blade architecture, multiple CPUs per blade with multiple cores per CPU – allow for a significant parallelization of application processes. The organization of data in columns supports the parallel use of cores for filtering and aggregation. Elements of application logic can be implemented as highly efficient stored procedures operating on columns. The vast increase in main memory combined with improvements in L1–, L2–, and L3-caching, together with the high data compression rate, column storage will allow us to support substantial data volumes on one single blade. Distributing data across multiple blades using a shared nothing approach provides further scalability.
Prof. Dr. h.c. Hasso Plattner is a co-founder of SAP AG, where he served as the CEO until 2003 and has since been chairman of the supervisory board. SAP AG is today the leading provider of enterprise software solutions. In his role as chief software advisor, he concentrates on defining the mid- and long- term technology strategy and direction of SAP.
Hasso Plattner received his diploma in communications engineering from the University of Karlsruhe. In recent years, he has been focusing on teaching and research in the field of business computing and software engineering at large. In 1998, he founded the Hasso- Plattner-Institute (HPI) in Potsdam, Germany. At the HPI, approximately 450 students are currently pursuing their Bachelors' and Masters' degrees in IT Systems Engineering with the help of roughly 50 professors and lecturers. The HPI currently has about 100 PhD candidates.
Hasso Plattner leads one of the research groups at HPI which focuses mainly on Memory-Based Data Management for Enterprise Applications and Human-Centered Software Design and Engineering.
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