Adding AI to your SQL workflow can be a revolutionary in terms of your efficiency, ability to troubleshoot, and navigate and query your databases. The boom of natural language model SaaS programs includes many new tools that work specifically with SQL.
What is an AI SQL tool?
An AI SQL tool uses artificial intelligence to simplify and enhance the process of managing, querying, and analyzing databases. These tools use natural language processing (NLP) and machine learning algorithms to enable you to interact with databases through conversational queries. A few things you can do with an AI SQL tool are:
- Natural Language Queries: AI SQL tools can translate natural language questions into SQL queries. This allows you to ask questions about their data in plain English, such as "Show me the total sales for last quarter" and get accurate results without writing any SQL code.
- Automated Query Generation: You are able to take existing SQL queries, or even plain language prompts, and leverage AI to fix, optimize, or suggest lines of code to improve accuracy.
- Data Insights and Visualization: AI SQL tools can often identify patterns, trends, and anomalies in data, and present these findings in easy-to-understand charts and graphs.
Adding the element of AI into a SQL tool serves the purpose of democratizing data for your company. Previously, without SQL knowledge, an employee would be reliant on a data literate team member to interpret results and answer questions for them.
The best AI SQL tools
AI 2 SQL is a useful tool for when you need an assist in building something that requires pulling in data. You ask the tool a query in plain language, and it will generate the correct SQL code you would need to put into your application in order to retrieve the correct data.
For example, if you needed to query information from your MongoDB logs, you could connect it to AI 2 SQL and then ask it plain language questions like, "How many error codes are in our logs?" or "Are there specific IP addresses associated with increased errors in our logs?" This information will help data scientists to clean up and ensure their data is more reliable.
SimplyPut, the makers of a conversations AI chat tool that allows you to query data in plain language and receive recommended insights, has developed a free SQL widget to help you debug SQL queries.
Input your error messages and the widget will return a code fix, explain the error code, or leverage AI to provide you with optimizations for performance and readability. The SQL tools widget also displays common error codes for you to quickly select to debug.
Use SimplyPut in the web app or Slack integration to connect your data sources and give everyone at your company the ability to ask the database plain language questions without needing a data engineer to dig up the answer.
Codeium is a powerful tool that allows you to autocomplete, chat with, or even pin relevant context to your codebase. It works with SQL, as well as a wide array of other coding languages. It serves as something of a robot assistant to a software engineer, helping them to optimize their code and ultimately move faster.
One callout here is that for 1 individual user, they offer an entirely free plan forever. Quite a steal for a robust code assistant.
Similar to AI 2 SQL, SQLAI generates SQL code for you from plain language prompts. Using AI to interpret your inputs, the tool is sophisticated enough to understand the SQL prompts you will need in order to retrieve an answer in your database.
Similar to Codeium, Tabnine is another code completion app that works with a wide variety of coding languages, including SQL.
Tabnine offers a generous 90 day free trial, and after that the most basic plan is $12/month.
Leveraging an AI SQL tool can offer benefits in accuracy, faster decision-making, cost savings, and ultimately, smooth out data usage inefficiencies. Using AI can bridge the gap between data management and data accessibility for a larger percentage of people at a company, empowering everyone to make more data-driven decisions.
Stephen is a SimplyPut Co-Founder and former data scientist and analytics manager at Atlassian. He is passionate about all things data and excited to be working on SimplyPut to enable everyone to answer their data questions.
