A snapshot of public web services
ACM SIGMOD Record
QPipe: a simultaneously pipelined relational query engine
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Specifying and solving Boolean constraint problems in relational databases: a case study
Proceedings of the 44th annual Southeast regional conference
Physical Database Design: the database professional's guide to exploiting indexes, views, storage, and more
Semantics based buffer reduction for queries over XML data streams
ADC '08 Proceedings of the nineteenth conference on Australasian database - Volume 75
Active Integration of Databases in Grids for Scalable Distributed Query Processing
OTM '08 Proceedings of the OTM 2008 Confederated International Conferences, CoopIS, DOA, GADA, IS, and ODBASE 2008. Part I on On the Move to Meaningful Internet Systems:
Semantics of a runtime adaptable transaction manager
IDEAS '09 Proceedings of the 2009 International Database Engineering & Applications Symposium
Database optimization for novelty detection
ICICS'09 Proceedings of the 7th international conference on Information, communications and signal processing
Database optimization for novelty mining of business blogs
Expert Systems with Applications: An International Journal
REaltime ACtive heterogeneous systems: where did we reach after REACH?
From active data management to event-based systems and more
Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems
XML databases and beyond-plenty of architectural challenges ahead
ADBIS'05 Proceedings of the 9th East European conference on Advances in Databases and Information Systems
Data Management in a Connected World
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Database system architectures are undergoing revolutionary changes. Most importantly, algorithms and data are being unified by integrating programming languages with the database system. This gives an extensible object-relational system where non-procedural relational operators manipulate object sets. Coupled with this, each DBMS is now a web service. This has huge implications for how we structure applications. DBMSs are now object containers. Queues are the first objects to be added. These queues are the basis for transaction processing and workflow applications. Future workflow systems are likely to be built on this core. Data cubes and online analytic processing are now baked into most DBMSs. Beyond that, DBMSs have a framework for data mining and machine learning algorithms. Decision trees, Bayes nets, clustering, and time series analysis are built in; new algorithms can be added. There is a rebirth of column stores for sparse tables and to optimize bandwidth. Text, temporal, and spatial data access methods, along with their probabilistic reasoning have been added to database systems. Allowing approximate and probabilistic answers is essential for many applications. Many believe that XML and xQuery will be the main data structure and access pattern. Database systems must accommodate that perspective. External data increasingly arrives as streams to be compared to historical data; so stream-processing operators are being added to the DBMS. Publish-subscribe systems invert the data-query ratios; incoming data is compared against millions of queries rather than queries searching millions of records. Meanwhile, disk and memory capacities are growing much faster than their bandwidth and latency, so the database systems increasingly use huge main memories and sequential disk access. These changes mandate a much more dynamic query optimization strategy - one that adapts to current conditions and selectivities rather than having a static plan. Intelligence is moving to the periphery of the network. Each disk and each sensor will be a competent database machine. Relational algebra is a convenient way to program these systems. Database systems are now expected to be self-managing, self-healing, and always-up. We researchers and developers have our work cut out for us in delivering all these features.