Most organizations monitor and tune the performance of their databases. But the performance management steps taken are almost always reactive. Handling performance problems is truly an enterprise-wide endeavor. However, the task of enterprise database performance management frequently becomes the job of the DBA group. Every performance problem gets blamed on the database regardless of its true source cause. Possessing a sound understanding of the IT infrastructure enables organizations to respond effectively when performance problems arise.

Sahaa Solutions uses event-driven approach that can make performance management easier by automatically invoking pre-defined actions when specific alerts are triggered. For example, an alert can be set to proactively reorganize a database when it reaches its storage capacity.
All of this discussion is useful, but it begs the question: just what do we mean by the term database performance? You need a firm definition of database performance before you can learn ways to plan for efficiency. Think, for a moment, of database performance using the familiar concepts of supply and demand. Users demand information from the database. The database supplies information to those requesting it. The rate at which the database supplies the demand for information can be termed "database performance."

We use following five factors to manage the database performance: workload, throughput, resources, optimization, and contention.

The workload that is requested of the DBMS defines the demand. It is a combination of online transactions, batch jobs, ad hoc queries, data warehousing analysis, and system commands directed through the system at any given time. Workload can fluctuate drastically from day to day, hour to hour, and even minute to minute. Sometimes workload can be predicted (such as heavy month-end processing of payroll, or very light access after 5:30 p.m., when most users have left for the day), but at other times it is unpredictable. The overall workload has a major impact on database performance.

Throughput defines the overall capability of the computer to process data. It is a composite of I/O speed, CPU speed, parallel capabilities of the machine, and the efficiency of the operating system and system software. The hardware and software tools at the disposal of the system are known as the resources of the system. Examples: database kernel, disk space, cache controllers, and microcode.

The fourth defining element of database performance is optimization. All types of systems can be optimized, but relational databases are unique in that query optimization is primarily accomplished internal to the DBMS. However, there are many other factors that need to be optimized (SQL formulation, database parameters, etc.) to enable the database optimizer to create the most efficient access paths.

When the demand (workload) for a particular resource is high, contention can result. Contention is the condition in which two or more components of the workload are attempting to use a single resource in a conflicting way (for example, dual updates to the same piece of data). As contention increases, throughput decreases.

Try out database performance roadmap here