AutoAdmin “what-if” index analysis utility
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Automated Selection of Materialized Views and Indexes in SQL Databases
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
An Efficient Cost-Driven Index Selection Tool for Microsoft SQL Server
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Integrating vertical and horizontal partitioning into automated physical database design
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Tuning schema matching software using synthetic scenarios
VLDB '05 Proceedings of the 31st international conference on Very large data bases
To tune or not to tune?: a lightweight physical design alerter
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
eTuner: tuning schema matching software using synthetic scenarios
The VLDB Journal — The International Journal on Very Large Data Bases
Storage workload estimation for database management systems
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Physical design refinement: The ‘merge-reduce’ approach
ACM Transactions on Database Systems (TODS)
Self-tuning database systems: a decade of progress
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Bridging the application and DBMS profiling divide for database application developers
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
SimulPh.D.: A Physical Design Simulator Tool
DEXA '09 Proceedings of the 20th International Conference on Database and Expert Systems Applications
An object placement advisor for DB2 using solid state storage
Proceedings of the VLDB Endowment
Configuring resource managers using model fuzzing: a case study of the .NET thread pool
IM'09 Proceedings of the 11th IFIP/IEEE international conference on Symposium on Integrated Network Management
CoPhy: a scalable, portable, and interactive index advisor for large workloads
Proceedings of the VLDB Endowment
Compression aware physical database design
Proceedings of the VLDB Endowment
A call to arms: revisiting database design
ACM SIGMOD Record
Stochastic database cracking: towards robust adaptive indexing in main-memory column-stores
Proceedings of the VLDB Endowment
ReStore: reusing results of MapReduce jobs
Proceedings of the VLDB Endowment
Materialized view tuning mechanism and usability enhancement
ICDCIT'06 Proceedings of the Third international conference on Distributed Computing and Internet Technology
PerfXplain: debugging MapReduce job performance
Proceedings of the VLDB Endowment
Holistic indexing: offline, online and adaptive indexing in the same kernel
PhD '12 Proceedings of the on SIGMOD/PODS 2012 PhD Symposium
Kaizen: a semi-automatic index advisor
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Autonomous database partitioning using data mining on single computers and cluster computers
Proceedings of the 16th International Database Engineering & Applications Sysmposium
A storage advisor for hybrid-store databases
Proceedings of the VLDB Endowment
Optimizing adaptive multi-route query processing via time-partitioned indices
Journal of Computer and System Sciences
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Database Tuning Advisor (DTA) is a physical database design tool that is part of Microsoft's SQL Server 2005 relational database management system. Previously known as "Index Tuning Wizard" in SQL Server 7.0 and SQL Server 2000, DTA adds new functionality that is not available in other contemporary physical design tuning tools. Novel aspects of DTA that will be demonstrated include: (a) Ability to take into account both performance and manageability requirements of DBAs (b) Fully integrated recommendations for indexes, materialized views and horizontal partitioning (c) Transparently leverage a test server to offload tuning load from production server and (d) Easy programmability and scriptability.