Database Best Practices for SQL ServerIn order for organizations to better manage development projects and the teams that develop code, Quest Software offers a set of guiding principles based on a best practices methodology. Quest’s SQL Server domain experts Kevin Kline and Brian Oliver and Toad® for SQL Server’s loyal customer base were instrumental in developing the methodology. It provides a consistent, repeatable and measurable process that even novices can use to manage the database development process, while ensuring that the highest quality code is deployed to production.
By implementing Database Development Best Practices, Toad for SQL Server
- Reduces the amount of bugs and helps you to share settings, project files and queries
- Enables you to get up to speed quickly, build code faster and improve coding quality
- Reduces performance bottlenecks
- Ensures that you can maintain and administer your SQL Environment
- Brings applications to market quicker by ensuring that the code written is of the highest quality and scaled for production
Database Development Best Practices for SQL Server consists of the following three-step process and is automated by Quest’s Toad Development Suite for SQL Server:
Steps for Delivering the Highest Quality Code:
- Develop : Developers first define the measurements for code success. Next, they can quickly and easily write code based on the requirements provided. Then they debug stored procedures and apply formatting.
- Optimize: The automated SQL scanning enables users to identify SQL statements that could cause problems in production. It then analyzes and rewrites them automatically.
- Validate:Quest’s scalability testing technology allows users to stress test code with hundreds of simulated database user connections in a test environment. This unique tool validates that the code is optimized and will scale to production load levels.
With Quest Software’s Database Development Best Practices for SQL Server, which were built in collaboration with Quest Software’s own domain experts like Steven Feuerstein, Mike Ault, Bert Scalzo, Kevin Kline as well as our customers, development teams are empowered to build code faster and cleaner, with fewer bugs. The following three-step process, automated by Quest’s Toad Development Suite for SQL Server, can guarantee the deployment of high quality applications:
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Quest’s Database Development Best Practices for SQL Server approach begins with the individual developer that is working on a project team. These developers have access to a version control system that enables Team Coding and simplifies the sharing of code. Through Best Practices each developer can build code faster and cleaner, with fewer bugs by employing the following steps:
- Prepare – Define the measurements for code success by describing the tests required to verify implementation of functional requirements
- Write and Compile – Build the programs according to pre-defined project coding standards including code formatting
- Debug – Using an advanced source code debugger, quickly identify and fix the lines of code that are causing issues
- Optimize SQL Statements – Scan code for problematic SQL statements that may cause serious bottlenecks in performance and, with one click, find the most-efficient SQL alternative
Step two in delivering optimal code centers around optimization of the SQL statements themselves.
According to industry analyst at least 60% of database performance issues are SQL-related. By following this process, developers can write efficient SQL code the first time, every time, and avoid costly performance issues in production. This process begins with conducting a code review that analyzes code for correctness, maintainability and efficiency. Next, SQL that will potentially perform poorly is identified by Scanning SQL code.
Once problematic SQL has been identified, the only way to ensure that the most efficient SQL is deployed is to rewrite the statements in every way possible and determine which statement will perform best for the database environment.
Once the code has been tested and optimized, the code is promoted to Quality Assurance. Before deploying applications into production, it is critical to validate the code for production-like conditions such as user load. In order to validate that code will perform optimally in a production environment, scalability tests are performed to performance test SQL statements or T-SQL code. Critical SQL statements can be tested and optimized for scalability. This can be done either by simulating hundreds of database user users running the SQL statements or T-SQL code, or by replaying production workload on the server in a testing environment.
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