Using AI to optimize your SQL queries

How to quickly optimize SQL queries using artificial intelligence.

Published on Jan 17, 2024 by AirOps Team

When SQL queries aren’t optimized correctly, a few things can happen:

  • Queries execute slowly,
  • Slow queries cause delays in data analysis and decision making for downstream activities that depend on that query, and; 
  • Warehousing costs add up if you use Snowflake or another data warehouse that charges by compute, which directly affects your organization’s bottom line.

Luckily, you can optimize your SQL queries automatically, no need to manually test and optimize every query.

Data Sidekick: An AI data tool that optimizes SQL queries instantly

Data Sidekick is a new data tool from AirOps that’s powered by a series of data apps designed to give you data superpowers. 

With the SQL Query Optimizer AI data app you can input a query into Sidekick and generate a list of suggested improvements. It automatically identifies areas where the query could be optimized, such as recommended indexing, join types, and query execution plans.

In addition to automatically optimizing SQL queries, you can also use Sidekick’s collection of AI-powered data apps to:

  • Convert natural language to SQL 🪄
  • Explain, modify, and fix SQL queries 🔧
  • Suggest questions a database table can answer 🧐
  • Auto document table schemas ✍️

… and more. We’re always adding new data apps to the collection, too.

The best part? Sidekick is 100% free for individuals. You don’t even need a credit card to create an account or use the tool.

Work with data 10x faster.

Magically draft, correct, and explain SQL. Instantly write Python scripts. Free for individuals and small teams.

Curious about how Sidekick performs in the wild? Check out this feedback from Kyle Dempsey, Head of CX and Solutions Architecture at AirOps. ⬇

Before Sidekick, what was your process for optimizing SQL queries?
As an experienced SQL writer, I’ve optimized countless SQL queries throughout my career. Even with all of my experience, though, SQL optimization can still be a time-consuming task that requires lots of attention to detail, not to mention knowledge of indexing, join types, and query execution plans.

It’s not always easy to figure out the best way to optimize a query and make it run faster. Sometimes, small changes have a big impact on performance.
How has Sidekick changed the way you optimize SQL queries?
Because I don’t have to manually test and optimize my queries, Sidekick saves me a ton of time. It saves my employer money too, since the total cost of our data stack is reduced by eliminating inefficient compute costs.

Another benefit is that I have more headspace to focus on data analysis and decision making, instead of worrying about how to best optimize my SQL statements.

Work with data 10x faster.

Magically draft, correct, and explain SQL. Instantly write Python scripts. Free for individuals and small teams.