Hex Reviews & Product Details

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.

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.

Hex is the most impressive analytical environment I have used so far. What impresses me most is how effortlessly Hex connects SQL and Python dataframes, allowing for smooth transitions between the two. I also value the intuitive visualization tools, including tables, pivots, and charts, which are simple to use without any additional setup. The data caching functionality is another strong point, as is the ability to connect to and manage multiple databases at once. ONe more feature worth to be mentioned is Components. And the last but not least is easiness of transforming notebooks into published apps. Review collected by and hosted on G2.com.

Hex provides an excellent feature that allows you to reuse SQL query cells as CTEs in later SQL cells. However, this functionality comes with a frustrating drawback. When working in Notebook mode, you must execute the CTE cell before running the final query, which effectively doubles the execution time. Review collected by and hosted on G2.com.

I appreciate Hex for its impressive agent integration and the ability to seamlessly alternate between SQL and Python cells, which stands out as a killer feature for me. This functionality allows me to extract data and plot it immediately, significantly enhancing my workflow efficiency, especially in creating reports starting from raw data. The ease of the initial setup is another aspect I found commendable, as it was 'super'. Overall, Hex has been a valuable tool in my work, leading me to highly recommend it with a perfect score of 10 out of 10. Review collected by and hosted on G2.com.

I find that the kernel timeout messages in Hex could be clearer, which currently causes some confusion, especially when working under tight deadlines. Additionally, the publishing options available are not as comprehensive as they could be, which limits the flexibility and reach when sharing reports or results. Review collected by and hosted on G2.com.

I use Hex for a wide variety of analytics, data science, and data transformation tasks, which significantly broadens its applicability in my work. I particularly appreciate how Hex helps accelerate insights, auto-identify the correct datasets and joins, and analyze code for efficiency gains swiftly. The agent feature is incredibly powerful; it often gets me 80%+ of the way to completing a task very fast, allowing me to focus on manual edits or optimizations effectively. I have been using this agent since its release for a range of tasks, especially in writing Python code, and it continues to improve frequently. Moreover, I found the onboarding process very easy, which facilitated a smooth adoption of Hex in my workflow. Overall, I am highly satisfied with Hex and would wholeheartedly recommend it to others, as evidenced by my willingness to rate it a perfect 10 on the recommendation scale. Review collected by and hosted on G2.com.

I find the agent feature sometimes struggles to switch effectively between query and dataframe mode. This can be problematic, especially when specific tasks require distinct modes, such as using dataframe mode for particular operations or query mode for handling larger datasets efficiently. Additionally, the size of notebooks tends to grow rapidly, which is often due to the creation of multiple cells instead of optimizing or editing existing ones. This rapid expansion with 'dormant' disconnected cells makes it challenging for me to grasp the full scope of a notebook, leading to difficulties in understanding and additional time required to comprehend what the notebook is doing. Review collected by and hosted on G2.com.

I love using Hex for ad hoc analytics due to its native SQL connection, which simplifies data retrieval. The ability to seamlessly integrate Python within the platform is highly valued as it allows me to build and share tools with my colleagues efficiently. Hex's ease-of-use, particularly with data in AWS, significantly enhances my workflow by enabling rapid task completion without the need for exporting or additional file management in Python or SQL. The Python + AI assistant feature is fantastic; sometimes the AI anticipates my needs and improves my typing through forward-filling, making coding a smoother experience. I also appreciate the ability to use the embedded version of Hex within our internal analytics platform, consolidating notebooks in one location, which I find extremely helpful. The initial setup of Hex was very easy, and based on my positive experience, I would wholeheartedly recommend Hex to others. Review collected by and hosted on G2.com.

I dislike the CTRL+F functionality inside a cell in Hex. It does not allow me to search for instances within a large cell effectively. Instead, it requires me to use CTRL+F outside the cell, which then searches the entire notebook for the term, leading to inefficiencies in the workflow. Moreover, when using CTRL+F inside a cell, pressing ENTER does not take me to the next instance of the searched term automatically, which is an expected behavior that would greatly enhance usability. Additionally, limitations in the amount of datapoints that can be displayed with the native visuals is a bit restricting. I constantly work with data that has lots of rows and lots of points. If there would be some default behavior that would somehow display an aggregate, a rolling median, or something and warn me about it rather than just say "too many data points" it would be useful. I'm typically more interested in the trends. Review collected by and hosted on G2.com.