Do More Storage Engines Improve MySQL Database Performance?

One of MySQL’s most appealing aspects is its ample support for several storage engines. At first glance, it is certainly wonderful for users of different needs gaining the ability to run the same top-notch SQL interface, yet store their data in various ways easily. 

While this seems great in theory, such functionality actually equals a substantial reduction in performance as well as an increase in the complication of operations and development. In this blog, we will discuss some of these complications that are brought on by this so-called selling point and why they may come in the way when users try to improve MySQL database performance in their organization.

How Multiple Storage Engine Compatibility Doesn’t Let You Improve Oracle Database Performance

Take a look at the following issues that may arise due to the interface on different storage engines - 

• Synchronization - MySQL’s top-level files require synchronization with engine transactions that get quite expensive on the performance front. What’s more, it can increase complexity and not let you improve Oracle database performance properly. These files include binary log docs and files with a “.frm” extension, and they require numerous “fsync()” calls for each transaction commit performed to maintain integrity.

• Transaction Assistance - Each storage engine may own a separate locking strategy and different combinations of locks. These can get even more intricate if we consider cross storage engine transactions.

• Operations - Tasks such as maintaining backup and keeping an eye on data get complicated enough, now they are accompanied by resource allocation and balancing through various storage engines. This complicates things. 

• Optimization and Implementation - Every storage engine has its own specifications which bring many differences, especially if we compare memory storage engines to distributed storage engines. 

Also, if we attempt to manage a variety of cases to improve MySQL database performance, using functions such as clustering by PRIMARY KEY or others depending on the nature of the storage engine - memory vs. distributed - makes data execution more cumbersome than it needs to be. Moreover, queries to perform such tasks need to be tuned for optimal performance, regardless of the storage engine.

• The Certainty of Quality - Many of the storage engines available these days are difficult to test, which is why hardly any of them are ever completely tested. This is also because there are myriad combinations of activities like executing updates on several tables, joining tables of different kinds, and so on, that will take plenty of time and effort to do so.

• Converting Data Formats – To access the data present in the storage engines, MySQL needs to do a lot of copy and conversion executions. This is because every storage engine owns a separate data storage format, which also affects the way users try to improve Oracle database performance. 

The conversion severely restricts performance in comparison with a design that involves negligible copying or converting while streaming information. 

• Creating and Storing Reserve Copies of Data - This is another aspect that suffers because of the differences in each storage engine - while some are in-memory storage engines, while others are distributed. 

Maintaining backups can be frustrating because the same level of approach cannot be used for all of them; they won’t work in all cases. 

CONCLUSION 

Interestingly, over ninety percent of applications are content with a single storage engine in terms of operability. In fact, most users intentionally avoid using multiple kinds of storage engines at the same time on a regular basis because they are already aware of the possible difficulties involved.