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The pressures on database developers have never been greater, and modern requirements for database efficiency are becoming more intense. SQL is a complex programming language, and the variability in the language can make for inefficient execution.
If SQL is not developed with efficiency in mind, then further down the line, performance can be drastically affected in other areas. If improper code goes unchecked into production, then external problems can arise, with delayed response times, and significant downtime, which can be costly for a company. Worse still is the fact that locating and solving problematic or inefficient code is a far costlier process once the PI/SQL has been implemented within the system. Locating the problem can take a long time, which requires specific skills that come at a price, with results that cannot give a long term guarantee. This, alongside the dynamics of database applications, with constant updates and fine-tuning to ensure efficiency, makes the process fraught with danger.
If the problems can be routed in the development process, this in most cases eliminates these issues for companies and organisations alike. Indeed, it is well known that 80% of problems in the Oracle environment can be prevented by the optimal coding of SQL and other related source code. This is where data optimization for Oracle comes in. SQL optimization is designed to make sure that SQL performance is at its highest, in the production environment, before it's taken for application. The optimization process is built to intelligently scan through PL/SQL and other source code, in a way similar to a human optimization expert, by actively screening for inefficient code, replacing the code, and testing the new code for performance.
SQL optimization specifically scans through multiple SQL statements, and checks for warnings of poor performance. It changes the code reversibly, while displaying the new code. It also gives a query of every other possible coding plan, from most optimal, to least optimal. It also allows the user to see if other alternatives may be more suitable for their specific environment, and also to test within a database environment to check efficiency. It can also export newly written SQL for usage. This optimization regime allows for high quality and reliable performance testing, before database application.
Optimization is ideal for DBA's, who need to meet certain criteria, through constantly upgrading and configuration changes. Poor SQL is a nightmare for administrators, and SQL optimization allows them to easily target issues in performance. Optimization is also flexible, and can be integrated into other database types, for multiple implementations and testing.
SQL optimization is designed as a tuning tool, for future proof, and to insure against costly downtime in your runtime environment. The usage of SQL optimization allows developers to concentrate on other important aspects, such as application functionality, while not having to waste time on optimization. User experience suggests that the benefits of optimization are vast, with no small effect on system efficiency and application performance, and reliability.[Author: Sara Selan]
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