Selection conditions in main memory
ACM Transactions on Database Systems (TODS)
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Technical perspective: One size fits all: an idea whose time has come and gone
Communications of the ACM - Surviving the data deluge
Queue - Scalable Web Services
Shore-MT: a scalable storage manager for the multicore era
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
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
Analyzing the energy efficiency of a database server
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
FAST: fast architecture sensitive tree search on modern CPUs and GPUs
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Memory-efficient frequent-itemset mining
Proceedings of the 14th International Conference on Extending Database Technology
Efficiently compiling efficient query plans for modern hardware
Proceedings of the VLDB Endowment
High performance database logging using storage class memory
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
High-performance concurrency control mechanisms for main-memory databases
Proceedings of the VLDB Endowment
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The efficient and flexible management of large datasets is one of the core requirements of modern business applications. Having access to consistent and up-to-date information is the foundation for operational, tactical, and strategic decision making. Within the last few years, the database community sparked a large number of extremely innovative research projects to push the envelope in the context of modern database system architectures. In this paper, we outline requirements and influencing factors to identify some of the hot research topics in database management systems. We argue that---even after 30 years of active database research---the time is right to rethink some of the core architectural principles and come up with novel approaches to meet the requirements of the next decades in data management. The sheer number of diverse and novel (e.g., scientific) application areas, the existence of modern hardware capabilities, and the need of large data centers to become more energy-efficient will be the drivers for database research in the years to come.