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Top 5 SQL AI Tools to Ease Writing SQL 2023

Mila
Mila4 min read
Top 5 SQL AI Tools to Ease Writing SQL 2023

Check out the 2024 edition.

If you work with data and databases, SQL AI tools can significantly improve your productivity and efficiency. Say you are a data analyst, data scientist, developer, or DBA, wouldn't it be great to have SQL queries generated automatically from natural language input (perfect for data analysts!), or have query performance optimized? If you want to start learning SQL, this is also an excellent way to get started.

Here we gathered some of the most popular SQL AI tools on the market.

AI2sql.io

AI2sql is an AI-driven SQL query generator, which means you can use natural language to instruct AI2sql to complete SQL queries. AI2sql has been around since 2021, way before the AIGC wave arrived. Recently, it has also integrated with OpenAI's GPT-3. Compared to ChatGPT, AI2sql is designed explicitly for querying databases or generating SQL queries. It supports the most popular databases on the market such as MySQL, PostgreSQL, MongoDB, Oracle, etc.

Product Hunt really is the go-to place for product releases, all tools featured today was submitted to Product Hunt at some point, let's also take a quick look at how they performed.

AI2sql's first launch in 2021 on Product Hunt ranked fifth for the day (which must have been quite impressive at the time). Two years later, version 2.0 was introduced with ChatGPT capabilities and received 142 Upvotes.

AI Query

AI Query uses the GPT-3 model to generate SQL queries from natural language. It currently supports database types such as Postgres, MySQL, MariaDB, and SQL Server, with plans to include others in the future (taking notes from this genius marketing approach).

What sets it apart from other AI tools that help you write SQL is its visual interface, which allows you to define the structure of database tables directly.

AI Query was launched on Product Hunt just one month after ChatGPT was released (at the end of November 2022).

Outerbase

Outerbase was released earlier this year and can be used on top of Postgres, MySQL, and most relational databases. Outerbase has a super modern and minimal interface compared to traditional database management tools. The user experience is similar to that of a spreadsheet. Although it also has AI-enhanced capabilities to assist with writing SQL and gaining insights from the database, it feels more like a SQL client designed for data analysts and business users.

Since its release on Product Hunt and Hacker News earlier this year, they haven't updated their Changelog since April, nor have there been updates on their social media channels. We wonder what happened?

SQL Chat

SQL Chat brings SQL clients from the traditional GUI-based stage to the CUI (Chat-based UI) stage: it integrates with ChatGPT to help you write SQL (and of course, answer any questions about databases!). It currently supports MySQL, PostgreSQL, SQL Server, and TiDB Serverless. And if you connect SQL Chat to your own database, it can write more accurate SQL queries.

Recently, SQL Chat introduced a subscription model (If you don't have an OpenAI account, you can still enjoy SQL Chat!) and the option to choose between GPT-3.5 or GPT-4 models.

Since its launch on Product Hunt, SQL Chat has gained significant attention.

TEXT2SQL.AI

Supply your database schema to Text2SQL.AI, choose the database you are using (MySQL, PostgreSQL, Snowflake, BigQuery, MS SQL Server), and Text2SQL.AI will generate the corresponding SQL for you.

When compared with other SQL AI tools, their website that besides being affordable (current price is $4/month for 300 requests), it is also the only tool capable of generating SQL as well as regular expressions, Excel and Google Sheets formulas (again, perfect for business analysts who need to work with Excel and data all the time!).

AI products are all over the place this year, but Text2SQL.AI was the #1 Product of the week in the AI category on Product Hunt when it was released.

What We Think

SQL AI tools are the best: they can improve efficiency, save us time and effort, and make it easier to interact with databases. However, they are not perfect. Although they also use state-of-the-art natural language processing models, the results may sometimes be inaccurate. And if you want to use them in production, make sure to double-check before you hit RUN.

On the other hand, if you are not ready to jump to the AI ship, below are the traditional options for you:

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