“One size fits all” database architectures do not work for DSS
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Building the Operational Data Store
Building the Operational Data Store
Patterns of Enterprise Application Architecture
Patterns of Enterprise Application Architecture
Olap Solutions: Building Multidimensional Information Systems
Olap Solutions: Building Multidimensional Information Systems
Multiclass Query Scheduling in Real-Time Database Systems
IEEE Transactions on Knowledge and Data Engineering
Towards Automated Performance Tuning for Complex Workloads
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
"One Size Fits All": An Idea Whose Time Has Come and Gone
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Dynamo: amazon's highly available key-value store
Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles
DBMS workload control using throttling: experimental insights
CASCON '08 Proceedings of the 2008 conference of the center for advanced studies on collaborative research: meeting of minds
A common database approach for OLTP and OLAP using an in-memory column database
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Overview of TPC Benchmark E: The Next Generation of OLTP Benchmarks
Performance Evaluation and Benchmarking
Normalization in a mixed OLTP and OLAP workload scenario
TPCTC'11 Proceedings of the Third TPC Technology conference on Topics in Performance Evaluation, Measurement and Characterization
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Database systems in the context of business data processing are segmented into two categories: those intended for online transaction processing (OLTP) and those for online analytical processing (OLAP). Over the last 15 years, database management system (DBMS) proposals directly addressing one of those categories were most represented in terms of academic publications and variety of commercial products in the domain of enterprise computing. In contrast, the most innovative DBMS proposals in this century were invented not by addressing a well-known category but by following a methodology that purely focuses on the application characteristics as practiced by Amazon or Google. This paper applies a part of that methodology to the field of enterprise applications in order to evaluate to what extend they are covered by the categories OLTP and OLAP. The evaluation shows that there are enterprise applications that reveal a mix of those characteristics which are usually exclusively associated either with OLTP or with OLAP and therefore cannot be addressed adequately by traditional DBMS. The paper contributes by pointing out that those applications cause an online mixed workload and by explaining what properties a corresponding specialized DBMS should have and how this category of enterprise applications could benefit from it.