Tool Evaluation Series: Hex
Hex is a collaborative, interactive notebook environment using SQL, Python, or no-code. It can be used for analysis but also to create data apps in a cell structure much like Jupyter Notebooks. I will evaluate Hex in terms of expanding data analytics capabilities to a more general audience — defined as the audience outside of data teams that may not be highly trained in data but want to use it to answer their own business questions without having to wait for the data team to answer them. Or in other words “Is Hex a good self-service tool?”.
The way I will do this is by defining a few criteria that I care about and using Hex to see how well it fulfills that criteria. The criteria will be:
- Setup & Maintenance: is the tool easy to set up, maintain, and learn?
- Useful Features: what are 3+ things that make this tool stand out?
- Cost: how expensive do I think this tool is? I define expensive as “Does this cost me as much as Tableau?”
- Audience Fit: do I think the tool fits my intended general audience?
1. Setup & Maintenance
Hex is a web-based application where you can connect to databases online so it’s very easy to set up. No installation required so you can get Hex up and running in minutes. A running list of supported databases is here and I am looking for Trino support for my organization, which is included.
Maintenance should be low due to no installation and there are plenty of reference guides and tutorials to learn from in the docs.
5 out of 5 points
2. Useful Features
- Notebook architecture: Hex works in a cell-based architecture much like Jupyter Notebook but you can actually write cells in SQL or Python within the same notebook.
- Cell Components: There are many different components and inputs for customization, including dbt Semantic Layer integration and database writeback
- Rich charts: Create charts as a cell from dropdown menus. There are 12 chart types to choose from and you can customize the style. I don’t think you can create custom chart types though.
- History through version control: Version control and Git sync of notebooks is sorely needed in modern data and BI tools and comes with Hex.
- Magic AI: AI is all rage these days and Hex is no exception. You can use the Magic actions to assist with analysis through natural language processing, which would be very helpful if you are not already familiar with SQL or the structure of the dataset.
Hex is clearly feature-rich and has tons of modern capabilities. It just feels nice to use it and was made by people who clearly have lots of experience in the data analytics/science field who understand workflows.
5 out of 5 points
3. Cost
Ooh boy, there’s always a catch with a tool this nice. Expanding Hex to a more general audience means we would probably grow past the Professional license pretty quickly. The Team license is just as expensive as a Tableau Creator license at $75 per user per month so you’re not saving any money in terms of licenses (server cost is a different story). Not a cheap tool by any means, especially when scaled.
2 out of 5 points
4. Audience Fit
Do I think Hex fits my general audience? Simply put, no. I think Hex is one of the most stylish tools I evaluated in this series with many different customizations and cool features like dbt Semantic Layer integration and Magic AI assist that can write SQL queries for you. If it was just the engineering team or my company was smaller, then I think it could be a fit but not with a more general audience that really just needs basic SQL or to know how to create and click filters. It would be a hard sell at this price point. Hex seems well-built to combine with dbt Cloud as well which is an additional cost as a prerequisite.
3 out of 5 points
Verdict
I really liked playing around with Hex. It’s a tool with a high degree of polish and care put into it by people who understand how data analysts and scientists work. It might be a better fit for a smaller company or more limited team within a company but not for an audience without a background in data. Hex has many modern features that fit well within the Modern Data Stack that I would recommend for the right team.
15 out of 20 points
