Hex Reviews & Product Details

I appreciate how easy it is to create custom reports and analyses, ranging from simple descriptive statistics to more advanced analytics. As a data developer at my company—combining aspects of both data engineering and analysis—I really enjoy coding in notebooks. We use BigQuery as our datawarehouse so the integration was so easy. Additionally, since I serve as the admin for our Hex account, I find the platform’s user-friendly interface for management to be a major advantage. I’d also like to mention that whenever I’ve needed support, whether for questions or to resolve bugs, customer support has always provided helpful answers or solutions. Review collected by and hosted on G2.com.

As a developer, I can't say that there's anything I currently dislike about Hex. However, from an admin perspective, I wish there were more detailed statistics available about users and their interactions with the platform. At the moment, I can only access limited information, such as users' most recent views, but I don't have a comprehensive overview of the entire user experience within this tool. Review collected by and hosted on G2.com.

It's very straightforward to start writing analyses, and to host them on the internet for others to see. The provided interactive elements also make it possible to write dashboards to help automate simple business processes that require human input. This part of the review is short and sweet because, for suitable use cases, Hex is very powerful and intuitive! Review collected by and hosted on G2.com.

This is more of a business process issue than a Hex issue, but here goes: It is important to scope out your project before starting with Hex. Once the number of cells in a project begins to swell (~70+ cells), the optimizations for notebook visuals become an editing problem. Ctrl-F will fail to take you to the correct cell, and trying to scroll up or down through the notebook becomes very sluggish as every cell you scroll over takes time to load, as they are unloaded once they are far enough away from the viewport. I cannot find a good workaround for this issue. Additionally, there is no multiline find-and-select, which can make refactoring code an enormous pain, especially when coupled with the notebook size issue. Review collected by and hosted on G2.com.

It is so easy to combine SQL with Python! I love how accessible it is to call variables created in different cells. The charts and pivot tables tools also work great and are very intuitive. Review collected by and hosted on G2.com.

This is probably related with my subscription tier, but I cannot work with tables with millions of rows, so I need to reduce my datasets early in the projects, which may be a bit limiting sometimes. Review collected by and hosted on G2.com.

It's a great tool for data scientists. Very easy and intuitive to use and the chart functionality makes data exploration super fast. Integration with our cloud warehouse has also significantly reduced data engineering burden. I use it everyday for work and even my coworkers who aren't technical are able to use Hex with the AI assistant. Review collected by and hosted on G2.com.

Chart options are a bit limited, but the main ones are still there. Also some of the custom measures/dimensions functions in Looker such as row totals, etc. Review collected by and hosted on G2.com.

I love using Hex to create dashboards and product analyses. I particularly appreciate the quick access to data and the simplicity of creating impactful and clear visuals. What I like the most is its blend between a Jupyter notebook and a classic reporting tool like Looker or Tableau. This allows me to quickly retrieve a figure that interests me and calculate new metrics, which facilitates rapid iteration compared to other more cumbersome tools. The initial setup was really simple and intuitive to connect to the database. I would give it a 10 out of 10 for recommending it to a friend or colleague. Review collected by and hosted on G2.com.

Even though they are good, I find the chart options too simplistic with little room for maneuver. I would like more chart styles, like Gantt for making funnels, and more options in the most used charts. Review collected by and hosted on G2.com.

I really enjoy how easy it is to create dashboards with Hex. The ability to flip between SQL and Python is fantastic because I can use the code that's best suited for the task at hand. The easy drop-down for charts and drag-and-drop features for charting and pivot tables make it a lot quicker than using pure Python or notebooks. The charts are far more visual and effective than those in Looker, and Hex is far cheaper than Tableau, which is great. The ability to see which parts of the code are taking longer than others is also brilliant as it often easy to speed up applications during test runs with some simple data editing. Review collected by and hosted on G2.com.

The charting library could be expanded. It would be incredibly helpful to have slightly more options to choose from, and for certain charts to be slightly less rigid in their structure. While certain charts can be created with python scripts, these always look significantly different in the app to those auto created by by the hex charting library. Expanding the library would speed up certain dashboard building as well as improving the visuals. For example, funnel charts would be a great addition. The notifications are a really cool function. However, they seem more suited towards a backend team suggesting that this run of the application has failed or succeeded, rather than a general updating for a company-wide or even a C-suite level view for things like daily or weekly updates on metrics. If the notifications were improved in that respect, and the charts could be pulled directly into it rather than from a PDF, it would be a really top-level tool. Review collected by and hosted on G2.com.

I quite like the notebook to app workflow and sharing capabilities. Creating a notebook from scratch, building out a replicable analysis, and sharing that with colleagues is a breeze with Hex. The SQL caching feature is quite nice as well to allow for faster notebooks coupled with sharing. Review collected by and hosted on G2.com.

You can redefine variable names in different cells. This leads to one of Hex's main features not executing well. A traditional jupyter notebook runs top to bottom sequentially. With Hex, a graph is created. If I want to run the 30th cell then Hex uses the graph to understand what stale cells above it should also be run. This is great, until you redefine variables in different cells which leads to less of a gain from this feature. Review collected by and hosted on G2.com.

I like that Hex combines the usage of SQL and Python, unlike Jupyter notebooks. It has an easier way of creating charts, pivots, and tables. The pivot feature with calculated columns is the one I find most helpful, and the chart cells as well. These features save me a lot of time because I would have had to write code to perform these actions otherwise. The Pivot Hex cell is great because even a non-technical person can just drag and drop to adjust things. I found the initial setup fairly easy due to the documentation. Review collected by and hosted on G2.com.

Sometimes the cells cause errors without any changes to the code or formula, which is frustrating because there's nothing to debug. This annoys me a lot. Also, there could be more chart types available for a more detailed analysis. Review collected by and hosted on G2.com.

- great visualization options

- highly flexible, dependency awareness between cells is very strong

- easy transition between python and sql

- responsive and kind customer support / team

- fast moving company, they keep adding new and useful features all the time

- easy to use

- reusable code components

- best AI integration in an analytics tool so far (still behind an experience like cursor though) Review collected by and hosted on G2.com.

- github integration is weak. I wish it was possible to push changes via github. For data analysis and exploration hex is quite good but I also use it for internal tooling since it supports python and for those use cases I prefer to write code in cursor and push to hex.

- auto complete could have been much better

- cells that return "query" (instead of dataframe) is a great idea but the implementation is not good. It tries to show you a sample of data so if your query has heavy joins it takes forever. because of this, for reusable CTE's I need to use python which is not a seamless experience Review collected by and hosted on G2.com.

I'm using Hex on a daily basis. It's very intuitive. I haven't done hands on data work in awhile and Hex made it easy for me to jump back in. Using the integrated AI I was able to find the information I wanted and it was helpful in extracting the information I needed quickly. It also made it easy to create quick apps using sql and python, schedule a job and integrate with other systems. Review collected by and hosted on G2.com.

Working with other data clients, I remember one helpful feature was the results have been saved in tabs. In Hex, every time I run a query it overwrites the previous results. Would have been nice to still see them in a tab. Review collected by and hosted on G2.com.