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Asked: 2026-05-11T05:59:32+00:00

What are the best practices for optimizing a MySQL installation for best performance when

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What are the best practices for optimizing a MySQL installation for best performance when handling somewhat larger tables (> 50k records with a total of around 100MB per table)? We are currently looking into rewriting DelphiFeeds.com (a news site for the Delphi programming community) and noticed that simple Update statements can take up to 50ms. This seems like a lot. Are there any recommended configuration settings that we should enable/set that are typically disabled on a standard MySQL installation (e.g. to take advantage of more RAM to cache queries and data and so on)?

Also, what performance implications does the choice of storage engines have? We are planning to go with InnoDB, but if MyISAM is recommended for performance reasons, we might use MyISAM.

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  1. The ‘best practice’ is:

    1. Measure performance, isolating the relevant subsystem as well as you can.
    2. Identify the root cause of the bottleneck. Are you I/O bound? CPU bound? Memory bound? Waiting on locks?
    3. Make changes to alleviate the root cause you discovered.
    4. Measure again, to demonstrate that you fixed the bottleneck and by how much.
    5. Go to step 2 and repeat as necessary until the system works fast enough.

    Subscribe to the RSS feed at http://www.mysqlperformanceblog.com and read its historical articles too. That’s a hugely useful resource for performance-related wisdom. For example, you asked about InnoDB vs. MyISAM. Their conclusion: InnoDB has ~30% higher performance than MyISAM on average. Though there are also a few usage scenarios where MyISAM out-performs InnoDB.

    The authors of that blog are also co-authors of ‘High Performance MySQL,’ the book mentioned by @Andrew Barnett.

    Re comment from @ʞɔıu: How to tell whether you’re I/O bound versus CPU bound versus memory bound is platform-dependent. The operating system may offer tools such as ps, iostat, vmstat, or top. Or you may have to get a third-party tool if your OS doesn’t provide one.

    Basically, whichever resource is pegged at 100% utilization/saturation is likely to be your bottleneck. If your CPU load is low but your I/O load is at its maximum for your hardware, then you are I/O bound.

    That’s just one data point, however. The remedy may also depend on other factors. For instance, a complex SQL query may be doing a filesort, and this keeps I/O busy. Should you throw more/faster hardware at it, or should you redesign the query to avoid the filesort?

    There are too many factors to summarize in a StackOverflow post, and the fact that many books exist on the subject supports this. Keeping databases operating efficiently and making best use of the resources is a full-time job requiring specialized skills and constant study.

    Jeff Atwood just wrote a nice blog article about finding bottlenecks in a system:

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