7 Ways to Optimize Your SQL Queries for Production Databases

According to Google, 53 percent of mobile users will abandon a website if it doesn’t load within three seconds — and the bounce rates for PCs and tablets aren’t that much more. So what do these stats mean for coders? Ultimately, they’re a stark reminder that crafting optimized SQL queries for production database environments should be a priority.

What Are SQL Queries and Production Databases?

New programmers may be wondering: What are SQL queries and production databases? At first, the terms may sound intimidating. But the reality is simple: SQL queries are simply the code you write to extract desired records from a database, and a production database just means “live data.”

In other words, a dynamic website that’s live and accessible is likely working off a production database.

Why Should SQL Queries Be Optimized?

Which would you rather read: a loquacious tome freighted with filler words and pretentious tangents or a tl;dr summary that zeros in on the topic at hand? Moreover, which would take longer to digest?

The same keep-it-simple logic applies to writing in SQL: the best queries are short, sweet, and get the job done as quickly as possible — because cumbersome ones drain resources and slow loading times. Plus, in the worst-case scenarios, sloppy queries can result in error messages, which are UX kryptonite.

Seven Ways To Optimize SQL Queries for Production Databases

#1: Ask the Right Questions Ahead of Time

Journalists have long understood the importance of who, what, when, where, and how. Effective coders also use the five questions as a framework. After all, every business has a purpose, and, like a finely tuned car, every mechanism should support the company’s ultimate goal — even the SQL queries that power its websites, databases, and reporting systems.

#2: Only Request Needed Data

One significant difference between novice programmers and experienced ones is that individuals in the latter category write elegant queries that only return the exact data needed. They use WHERE instead of HAVING to define filters and avoid deploying SELECT DISTINCT commands unless absolutely necessary.

#3: Limit Sources and Use the Smallest Data Types

If you don’t need a full report of matching records, or you know the approximate number of records that a query should return, use a LIMIT statement. Also, make sure to use the smallest data types; it speeds things up.

#4: Be Minimalist, Mind Indexes, and Schedule Wisely

Choose the simplest and most elegant ways to call up needed data. To state it differently, don’t over-engineer. Moreover, make use of table indexes. Doing so speeds up the query process. Plus, if your network includes update queries or calls that must be run daily, schedule them for off-hours!

#5: Consider Table Sizes

Joining tables is an SQL query staple. When doing it, make sure to note the size of each table and always link in ascending order. For example, if one table has 10 records and the other has 100, put the former first. Doing so will return the desired results and cut down on query processing time.

#6: Only Use Wildcards at the End

Wildcards can be a godsend, but they can also make SQL queries unruly. By placing them at the beginning and end of a variable, you’re inefficiently forcing the broadest possible search. Instead, get specific. And if you must use a wildcard, make sure it’s at the end of a statement.

#7: Test to Polish

Before you put a project to rest, test! Try different combinations; whittle away at your queries until they’re elegant code blocks that make the least number of database calls. Think of testing as the editing stage, and revise until the work is polished.

Who Should Tweak SQL Queries?

People with little or no coding experience may be able to DIY a small CSS change or add an XHTML element without catastrophe. But SQL queries are a very different story, one errant move can wreak mayhem across your operations.

Optimizing SQL queries is essential in today’s digital landscape, and failing to do so can lead to decreased views and profits. So make sure to optimize the code before going live. And if you don’t have the experience, enlist the help of someone who does. It’s worth the investment.

Read more tactics on optimization here!

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Big Data & AI Enthusiast at Inzata Analytics

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Scottie Todd

Scottie Todd

Big Data & AI Enthusiast at Inzata Analytics

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