Physical database design for relational databases
ACM Transactions on Database Systems (TODS)
Extensible/rule based query rewrite optimization in Starburst
SIGMOD '92 Proceedings of the 1992 ACM SIGMOD international conference on Management of data
The COMFORT automatic tuning project
Information Systems
Strategic directions in database systems—breaking out of the box
ACM Computing Surveys (CSUR) - Special ACM 50th-anniversary issue: strategic directions in computing research
AutoAdmin “what-if” index analysis utility
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Microsoft index turning wizard for SQL Server 7.0
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Answering complex SQL queries using automatic summary tables
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Self-managing technology in IBM DB2 universal database
Proceedings of the tenth international conference on Information and knowledge management
Automating physical database design in a parallel database
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Adaptive and Automated Index Selection in RDBMS
EDBT '92 Proceedings of the 3rd International Conference on Extending Database Technology: Advances in Database Technology
A Rule Engine for Query Transformation in Starburst and IBM DB2 C/S DBMS
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
fAST Refresh using Mass Query Optimization
Proceedings of the 17th International Conference on Data Engineering
Automated Selection of Materialized Views and Indexes in SQL Databases
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
LEO - DB2's LEarning Optimizer
Proceedings of the 27th International Conference on Very Large Data Bases
Towards Automated Performance Tuning for Complex Workloads
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
DB2 Advisor: An Optimizer Smart Enough to Recommend its own Indexes
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Evolutionary techniques for updating query cost models in a dynamic multidatabase environment
The VLDB Journal — The International Journal on Very Large Data Bases
Goals and benchmarks for autonomic configuration recommenders
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Physical Database Design: the database professional's guide to exploiting indexes, views, storage, and more
Automated statistics collection in DB2 UDB
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
A new approach to dynamic self-tuning of database buffers
ACM Transactions on Storage (TOS)
An index selection method without repeated optimizer estimations
Information Sciences: an International Journal
An Ontology-Based Autonomic System for Improving Data Warehouse Performances
KES '09 Proceedings of the 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems: Part I
Automation everywhere: autonomics and data management
BNCOD'07 Proceedings of the 24th British national conference on Databases
Online monitoring and visualisation of database structural deterioration
International Journal of Autonomic Computing
Workload management: a technology perspective with respect to self-* characteristics
Artificial Intelligence Review
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As the cost of both hardware and software falls due to technological advancements and economies of scale, the cost of ownership for database applications is increasingly dominated by the cost of people to manage them. Databases are growing rapidly in scale and complexity, while skilled database administrators (DBAs) are becoming rarer and more expensive. This paper describes the self-managing or autonomic technology in IBM's DB2 Universal Database® for UNIX and Windows to illustrate how self-managing technology can reduce complexity, helping to reduce the total cost of ownership (TCO) of DBMSs and improve system performance.