Query based insertion or updating of blob values
They also generally require fewer CPU cycles to process.Make sure you don’t underestimate the range of values you need to store, though, because increasing the data type range in multiple places in your schema can be a painful and time-consuming operation.Good logical and physical design is the cornerstone of high performance, and you must design your schema for the specific queries you will run. For example, a denormalized schema can speed up some types of queries but slow down others.Adding counter and summary tables is a great way to optimize queries, but they can be expensive to maintain.My SQL’s particular features and implementation details influence this quite a bit.
My SQL supports a large variety of data types, and choosing the correct type to store your data is crucial to getting good performance.
The following simple guidelines can help you make better choices, no matter what type of data you are storing: In general, try to use the smallest data type that can correctly store and represent your data.
Smaller data types are usually faster, because they use less space on the disk, in memory, and in the CPU cache.
Some data types also have special behaviors or properties.
For example, a uses only half as much storage space, is time zone–aware, and has special autoupdating capabilities.