Metrics are relative, so without the proper context, they’re often meaningless. Traditional database management focuses on dashboards with countless confusing health metrics, while newer tools can offer context to look at performance data from multiple angles.
With SolarWinds® Database Performance Analyzer (DPA), you can easily invoke the right context filter and quickly filter down to a wait time for a specific SQL query within a program for deeper multi-dimensional database analysis.
Database performance tuning focused on reducing utilization of CPU, memory, storage, or the network can improve resource use, but doesn’t necessarily improve database performance.
By correlating database response time with resource metrics, DPA can show the link between resource contention, its effect on the database, and ultimately application performance. The VM Feature is also designed to provide a direct correlation between database response time, the physical host, and datastore for databases on VMware.
SQL Server wait types and Oracle, DB2, and ASE wait events are key to understanding the precise cause of slow SQL response times in multi-dimensional databases.
However, understanding waits can be difficult, which is why DPA includes a description of the wait, advice on how to best resolve the issue, and insight into who typically deals with the problem at hand to help improve DevOps collaboration between developers, IT generalists, and accidental DBAs. Database Performance Analyzer is also built to monitor these waits, so you can more easily identify those with the most significant impact on database performance.
Database management software products tend to neglect the most important aspect of performance: response time. The time between an application submitting a SQL statement and the database management system responding really matters to applications and end users.
By starting with response time, DPA focuses the context of all metrics and further analysis on areas that can deliver the biggest impact to improving the most important database metric: database response time.
Many factors influence SQL performance, including number of executions, plans, and locking/blocking. To truly understand SQL performance, database developers need to see how code works in production.
DPA places only a negligible load on production servers regardless of settings or view within the product. To help ensure the security of production performance data, the security settings and Active Directory integration in DPA provide multi-level permissions and group-based policies.
Do you find yourself asking…
While standard databases, like relational databases, are two-dimensional, cross- or multi-dimensional databases offer a variety of dimensions for data—three dimensions or more.
Conceptually, the multi-dimensional database structure is based around the idea of a data cube. Within this cube, every point of data is accessible by multiple indexes. This access is referred to as “online analytical processing (OLAP) access.” In practical terms, this means using a multi-dimensional database structure, as opposed to a standard database, gives you fast access to top-level, summarized data you can then drill down into if you want more detail.
Some of the advantages of using a multi-dimensional, cross-platform database structure as compared to a relational database are:
While standard databases, like relational databases, are two-dimensional, cross- or multi-dimensional databases offer a variety of dimensions for data—three dimensions or more.
Conceptually, the multi-dimensional database structure is based around the idea of a data cube. Within this cube, every point of data is accessible by multiple indexes. This access is referred to as “online analytical processing (OLAP) access.” In practical terms, this means using a multi-dimensional database structure, as opposed to a standard database, gives you fast access to top-level, summarized data you can then drill down into if you want more detail.
Some of the advantages of using a multi-dimensional, cross-platform database structure as compared to a relational database are:
Database Performance Analyzer
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