intro
An index in SQL is a friend to many developers and DBAs. Or is it? Find out everything you need to know about indexing in this blog!
Let’s face it — if you’ve heard about databases, you know your way around indexes. Some of you may know indexes better, some a little worse, but nonetheless, saying that many consider indexes one of your friends is no exaggeration. What is an index in SQL? How does it work? Why to use it? Time to find it out!
What are Indexes?
On a high level, an index in SQL is simply a data structure that helps quickly find rows. If you are a frequent reader of this blog, you will know that multiple types of database management systems offer multiple distinct types of indexing in SQL to choose from.
MySQLers will say that there are many indexes you can pick from. However, contrary to popular belief, indexes in MySQL aren’t categorized into many categories, but they fall into two instead — all indexes, no matter what your use case is, will be of one or the other type:
Other database management systems, especially those notorious for their widespread support of indexing (PostgreSQL, anyone?), offer a more feature-rich selection, but nonetheless, one thing remains: indexes are data structures that are used to quickly find data.
Types of Indexes
The types of indexes that are available in a particular database management system will be directly dependent on what database management system is in use. Contrary to a popular belief, non-relational database management systems like MongoDB also support indexing.
After all, indexing isn’t much different than in relational database management systems either. According to the docs, given that an appropriate index exists for a query, MongoDB would use the index to limit the number of documents it must scan.
However, for an index in SQL to be applied and used properly, we first must make adequate choices. In other words, we must choose an adequate index for our use case properly.
In this case, users of PostgreSQL will have a feature-rich choice menu, while users of other database management systems like SQL Server or MySQL will have fewer options to choose from, but that shouldn’t cause any issues no matter what database management system you find yourself using because:
A table depicting the types of indexes in various database management systems can be seen below:
| Database | Type | Index Specifics |
|---|---|---|
| MySQL/MariaDB/Percona Server | Relational (SQL) | All indexes that are not B-tree indexes are R-tree indexes. R-tree indexes are spatial indexes, and B-tree indexes include fulltext indexes, covering indexes, unique indexes, and other indexes. More information here. |
| SQL Server | Relational (SQL) | Various index types available for use, including clustered, non-clustered, hash indexes, unique and columnstore indexes, and more. More information here. |
| MongoDB | Non-Relational (NoSQL) | Wide support for indexing including single field indexes, compound indexes, multikey indexes, geospatial indexes, text indexes, hash indexes, and other types. All details available here. |
| PostgreSQL | Object-Relational | Widely known for its extensive support for data types, PostgreSQL supports several index types including B-tree, hash, GiST, SP-GiST, GIN, BRIN. |
Which Index to Choose and When?
With so many choices involving indexing, it’s only natural that people get lost in the jungle. It’s obvious that there are many choices you can employ, but nonetheless, choosing a proper index type is a challenge for many. Below, you will find some general guidelines advising you on how to choose an index type:
Besides these variables, there may be a couple of other things worthy of your consideration — these may include the load towards your database, client or employer requirements, and even the location of your server when it comes to CDN choices and the like.
Also keep in mind that SQL indexes make reading operations faster at the expense of slowing down INSERT, UPDATE, and DELETE operations because when data is inserted, updated, or deleted, entries in the SQL index need to be updated together with it. Discover more in our guide on 10x query performance with a database index.
However, no matter your choices and the situation you are in, there are a bunch of other things you need to think about when using an index in SQL databases.
Beyond Indexing — SQL Clients
One of the primary things necessitating your consideration would be related to SQL clients — you have to run your SQL queries somewhere, right?
Here’s where SQL clients like DbVisualizer come in — with its powerful auto-complete, query-building, visualization, and schema inspection capabilities (there are more!), it can help you to understand how, what, and when indexes are used in your database as well as provide you with powerful equipment to deal with all kinds of issues:
In the screenshot above, you see DbVisualizer’s ability to depict columns in a table. I would direct your attention to the fact that in this scenario, DbVisualizer is not only able to depict the fields and the indexes that they contain, but also provide you with a bunch of other information that you can act on.
In particular:
That’s a good chunk of information — and that information is only relevant to a very small part of your database, too! Now imagine having such an amount of information wherever you go.
Awesome, right? Why not try DbVisualizer today? Click here and receive a free 21-day trial of the software!
Summary
In SQL, an index is a data structure that acts like an index in a book helping your database (and, consequentially, your application) quickly find rows. A query that uses an index in SQL can be completed quicker because it can eliminate certain rows from consideration.
By choosing an index to assist your use case, you’re choosing a reliable friend that needs to be cared for — that friend, however, also promises you to make your query performance faster.
FAQ
What is an Index in SQL?
An index in SQL is a data structure that helps your database quickly find data. Using an index, a database is able to find data that the user asks for by acting pretty much like an index in a book.
What SQL index should I choose?
The exact type of index in SQL you will need to employ depends on multiple factors including what kind of a database management system you find yourself using, the index type, the amount of data stored in a specific table, what tables are accessed, your query structure, etc.
In most cases, you will use a B-tree index — however, the exact type of that index (covering, unique, vanilla, full-text, etc.) depends on the factors stated above.
Why should I use DbVisualizer?
Consider using DbVisualizer because it’s one of the most popular SQL clients that is available on the market today. DbVisualizer helps you with everything from visualizing the output of queries and automatically completing them to exporting your precious data in a variety of formats.
Learn more about DbVisualizer and start using it today!
Where can I learn more about databases?
To learn more about database management systems and things related to them, we advise you follow the documentation of your specific database management system in question, watch YouTube videos relevant to the subjects you want to learn, and read books.
We’ve provided examples on a database called “hacking_mysql” not without a reason — “Hacking MySQL: Breaking, Optimizing, and Securing MySQL for Your Use Case” is a book depicting indexes in MySQL and discussing other things that help you optimize and secure database instances. Learn more about the book here, and until next time.
