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Database tuning describes a group of activities used to optimize and homogenize the performance of a database.It usually overlaps with query tuning, but refers to design of the database files, selection of the database management system (DBMS) application, and configuration of the database's environment (operating system, CPU, etc.).
The performance of a query plan is determined largely by the order in which the tables are joined. For example, when joining 3 tables A, B, C of size 10 rows, 10,000 rows, and 1,000,000 rows, respectively, a query plan that joins B and C first can take several orders-of-magnitude more time to execute than one that joins A and C first.
SQL Performance Tuning by Peter Gulutzan, Trudy Pelzer (Addison Wesley, 2002) ISBN 0-201-79169-2 (Chapter 2, Simple "Searches"); Microsoft SQL Server 2012 Internals by Kalen Delaney, Connor Cunningham, Jonathan Kehayias, Benjamin Nevarez, Paul S. Randal (O'Reily, 2013) ISBN 978-0-7356-5856-1 (Chapter 11, The Query Optimizer)
Since SQL is declarative, there are typically many alternative ways to execute a given query, with widely varying performance. When a query is submitted to the database, the query optimizer evaluates some of the different, correct possible plans for executing the query and returns what it considers the best option.
Database tuning and performance monitoring. Application tuning and performance monitoring. Setup and maintain documentation and standards. Plan growth and changes (capacity planning). Work as part of a team and provide 24/7 support when required. Do general technical troubleshooting and give cons. Database recovery
See the main article at Performance engineering. Performance engineering is the discipline encompassing roles, skills, activities, practices, tools, and deliverables used to meet the non-functional requirements of a designed system, such as increase business revenue, reduction of system failure, delayed projects, and avoidance of unnecessary usage of resources or work.
Azure SQL Database includes built-in intelligence that learns app patterns and adapts them to maximize performance, reliability, and data protection. Key capabilities include: Learning of the host app's data access patterns, adaptive performance tuning, and automatic improvements to reliability and data protection. [3] Scaling on demand. [4]
The SQL specification defines what an "SQL schema" is; however, databases implement it differently. To compound this confusion the functionality can overlap with that of a parent database. An SQL schema is simply a namespace within a database; things within this namespace are addressed using the member operator dot ".". This seems to be a ...