How To Increase Database Efficiency

database efficiency

The overall performance of a database depends largely on its efficiency. Many factors can affect efficiency, including how indexes are used, how queries are structured, and how data is modeled.

Consequently, making small tweaks to any of these elements can have a significant impact. This database performance guide will review the basics to help make the best out of your database.

7 Ways to Increase Database Efficiency

1. Determine Database Purpose

Before designing it, it is necessary to determine the database’s purpose, organize and categorize its information, define the relationships between tables and elements to make the integration of the database with our systems easier. These initial steps will eliminate duplicates and will help us configure an efficient work methodology in the management of information in the future, and optimize database efficiency.

2. Clean up unused tables

No matter how well you make the initial approach to the database, over time, you probably end up having unused tables. Eliminate them for optimal database efficiency! Having unused tables is very similar to storing things you do not use in a drawer; you will not find what you want when you need it the most. The same happens with databases: the systems have to track all the tables and elements until it finds the answer to the query.

3. Optimal ratio of index to table

Having a good ratio of indexes between tables is basic for relational searches to work correctly. Add indexes to the tables and use the query statements (SELECT, WHERE …). It is also advisable to get used to periodically check the record of slow queries to identify those that should be optimized.

4. Drop Open Queries

Do not keep open queries in your code and perform the correct queries. Thus, you will avoid saturating the memory of the machine. As with any computer system, an open process affects the performance of the hardware. By eliminating those useless queries, you will free resources that can be later used in the queries you need.

5.  Minimize images in the database

In general, do not store images in the database, only store references to the route in which they are found and metadata to identify them. Make no mistake, the databases grow and grow, and the images continue to grow in size at their own pace. If you keep only the references to the stored image, the database will be in shape to return the processes more quickly.

6.  Simple names in keys and fields

Do not use complex names in the keys and fields of the tables. Simplify! For example, in the Customers table, it is better to use name instead of customer_name to store the customer’s name. The simpler the names, the faster the query is executed.

7.  Keep focussed

It is also advisable not to get carried away. Design a thoughtful approach to the hardware and software infrastructure that you need to adapt to the objectives and specifications of our project. Choosing a system initially conceived for a particular use may be better than going to the standard alternatives. For example, for concurrent uses, Nginx can provide a better result than Apache. Going out of the usual to have a better performance does not cost so much, and in this sense, the deployment of Cloud Servers can significantly facilitate the choice.
The more you know about database architecture, the better prepared you’ll be to make it work properly. Optimizing database performance isn’t a one-and-done deal. It requires diligence and ongoing communication between administrators and developers.

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