SQL Indexes Explained – MySQL Index Types (SQL Tutorial)

This shorts clip – a sql tutorial – will walk you through some of the basics of the basics of sql queries – sql index types. SQL basics are much more in-depth than just that, however, with sql indexes explained, one can obtain a lot of performance gains.

A MySQL index is a data structure that’s used to quickly find rows with specific column values. A SQL index can be used in any database management system – be it MySQL, its flavors like Percona Server or MariaDB, or Oracle, SQL Server, TimescaleDB, PostgreSQL, MongoDB, or even Sybase: the premise is the same.

Database indexes are something that must be known to every developer working on any sql project (any project that requires the usage of sql.)

Indexes help solve a multitude of database performance issues: they speed up SELECT SQL queries at the expense of slowing down INSERT and UPDATE SQL queries. Indexes can be very useful for database performance tuning, database performance testing, and database performance comparison. SQL indexes are also very widely used in database performance analysis as well as database performance monitoring.

By knowing their way around sql basics, both developers and DBAs will be able to make their work faster & more efficient.

Database indexes can be categorized into a couple of types:
1) Balanced tree (B-Tree) indexes – the most frequently used type of SQL index. This SQL index type can be used together with search queries that use the exact-matching and BETWEEN keywords, also with LIKE (wildcard) queries.
2) Spatial (R-Tree) indexes – can be used together with MySQL geometric data types to index geographical objects.
3) Hash indexes – usually used only with queries that use the exact search operators. Very fast but can be used only when the MEMORY storage engine is in use.
4) Covering indexes – SQL indexes that cover all of the columns required for a query to complete.
5) Clustered indexes – such SQL indexes store row data. Usually PRIMARY KEYs or, if they do not exist, UNIQUE indexes.
6) Multicolumn (composite) indexes – indexes that are created on multiple columns.
7) Prefix indexes – such indexes allow you only to index a prefix of a column. As such indexes do not index the full value of a column, they are frequently used to save space on the disk.

Choosing a good index type for your use case might be a hassle, however, once you understand the requirements of your project and the upsides and downsides of using certain indexes in MySQL, choosing the right SQL index becomes easier.

Want us to make a SQL tutorial or a SQL course on SQL injection or other security, performance or availability topics like database design, etc.? Perhaps we should explore SQL for beginners? Perhaps you’re interested in database normalization 1nf 2nf 3nf? Let us know in the comment section down below!

Also explore an older video about database slowness reasons here: https://youtube.com/shorts/tTE8DELShHw

Enjoy the video!

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