Reseñas y detalles del producto de Hex

Hex is a wonderful product. It is a souped Jupyter notebook with native SQL and some nifty dashboarding features. For people able to code is a far superior solution compared to point and click BI tools like Tableau and Power BI. Reseña recopilada por y alojada en G2.com.

The three things I feel most limited by are:

1. It would be really nice to be able to support Python packages like pymer4 that rely on an R instance to run. There are many statistical packages that are R only.

2. The R functionality is basic compared to what is supported in Python. Would liek to see that built out.

3. Hex is pretty limited computationally compared to even my local machine. I often run into a bottleneck in terms of pure computation. Reseña recopilada por y alojada en G2.com.

- Notebooks are very easy to share

- I feel like Hex works well in an environment where users have a mix of background with notebooks. It's just very easy to get up and running and collaborate

- This is probably the easiest/quickest tool I've used for generating dashboards and sharing it with broader teams Reseña recopilada por y alojada en G2.com.

Hex isn't super great for power users e.g. those who've been using the Python ecosystem for years:

- You can not control the Python kernel (the latest you can use is 3.10 which was released over 3 years ago...). Critical libraries like pandas/numpy are pinned to very old versions and you can not upgrade them

- The GUI editor for creating charts is great for business users and engineers who haven't spent 10+ years learning matplotlib 😂 but for someone who has, the whole plotting interface is quite limiting and adds a lot of bloat/latency to the notebook UI

- No plugin ecosystem like other notebook solutions. I miss being able to automatically lint/apply code formatters to my cells Reseña recopilada por y alojada en G2.com.

Hex is so helpful for visualizing data and translating complex data insights into easy to digest insights for non-technical stakeholders. I compare Hex to Looker a lot and I love the ability to dynamically construct queries to create visualizations that improve performance and run times.

I use Hex every single day and create 3-4 dashboards every 2 weeks for stakeholders. The Hex apps have been widely accepted by stakeholdes. Reseña recopilada por y alojada en G2.com.

Hex does have some limitations. I recently came across a need to separate permissions for different users within a single app between tabs. I believe the current workaround is to embed individual cells into a separate application for visualization but if Hex could allow for different user access within a single app, that would be really great! It is kind of a niche use case but would definitely be appreciated. Reseña recopilada por y alojada en G2.com.

As a new user, I am still getting familiar with HEX and all of its features/functions. I like the sharing capabilites, it really assists with seamless collaboration. I appreciate the new outline feature to help me stay organized. Reseña recopilada por y alojada en G2.com.

For me, the visualizations are a bit of a downside. I find myself constantly having to rewrite queries or use parameters (work arounds) to make simple visualizations or big number values that are really easy to do in Mode or Tableau. For instance, why not be able to add more series to y axis for grouped charts. For example, if I have 3 values I'm trying to show over time, my only option is to do one as a bar, one as a line, and can't do the other at all. And this is just for the left axis. If I want to do the combo, then I would have 2 lines and it wouldn't make sense and be confusing. Also, it would be helpful to add filters to visualizations where end users can't see them. Reseña recopilada por y alojada en G2.com.

Me encanta el clúster siempre conectado y la ejecución rápida de código en HEX, a diferencia de Databricks, donde siempre tengo que conectar los cuadernos al clúster para ejecutar cualquier código. He interactuado con el soporte al cliente una vez y fueron realmente útiles y fácilmente disponibles para ayudar a través de Slack. Encuentro fácil codificar e implementar una solución tanto en SQL como en Python en HEX sin muchas complicaciones. Soy científico de datos en Upwork y uso HEX casi a diario para trabajar en problemas de ciencia de datos usando Python y SQL. Encuentro la integración de los cuadernos de HEX con otras plataformas de almacenamiento como S3 bucket muy sencilla. Reseña recopilada por y alojada en G2.com.

Echo de menos la facilidad de desplegar cualquier cuaderno como una canalización y programarlo en forma de un flujo de trabajo en HEX. Reseña recopilada por y alojada en G2.com.

It's very clear that the developers and product team at Hex have interviewed a ton of data professionals and are making a really great tool. The recent addition of Sections is proof of that, the amount I had to scroll through my longer notebooks was 100% my biggest complaint. Compoments and other features like that add a ton of flexibility to hex, and the customer support has always been helpful whenever I've needed it. Reseña recopilada por y alojada en G2.com.

I still struggle with extremely large datasets in hex - being able to return sql cells as queries and other workarounds like that certainly help, but when returning the data as a pandas dataframe things get bogged down very quickly once there are more than 1 mil rows in play. My other complaint is that the charts are not the easiest to use - if I want to very quickly visualize a bunch of different slices of data I will frequently turn to another tool and then return to hex once that step of my process is done. Other than that there are just weird little bugs sometimes, like the order by clause in a sql statement not reliably returning results in the requested order. Reseña recopilada por y alojada en G2.com.

The notebook experience in Hex is unmatched when compared to other data visualization tools in same class (e.g. Mode, Tableau, and Hex). This is especially true for users that are comfortable with code e.g. Python, SQL, and R. Additionally, Hex integrates well with the most common data warehouse types e.g. Snowflake, Clickhouse etc. The native charts are also very helpful and generally Hex appears to prioritize support for visualization libraries in Python which helps to cover use cases outside of what is available in native Hex charts. Reseña recopilada por y alojada en G2.com.

The only item that keeps me from giving Hex a perfect 10 score is that my experience with customer support has never been really been great. I'm not exactly sure why, but Hex customer support always takes a while to respond and when I do get a response it typically isn't very helpful. I suspect that the customer support team doesn't have great visbility into the issues facing customers, but I am unsure.

That being said, other less significant issues I've run into are:

1) Attempting to use GPUs on Hex. My team tried to use a GPU instance but frankly was unable to due to issues with package / library management. Honestly though, GPU instances feel a bit odd on Hex to begin with, and there are many other service providers I would rather use for development on GPUs.

2) Hex Magic does not work well at all. I personally don't have a strong need for an embedded LLM / AI into my Hex notebooks, but any time I've actually tried to the Hex Magic feature it often underperforms when compared to base ChatGPT. This is coming from someone who uses LLM / AI regularly and also develops applications that leverage LLM / AI. I suspect something is off with the underlying evaluation approach / pipeline. A good Hex Magic experience would feel like using Cursor, where the model understands the full context of the project. Reseña recopilada por y alojada en G2.com.

Me encanta que Hex ofrezca la capacidad de integrar datos de Snowflake en un IDE similar a un cuaderno de Jupyter, para que pueda crear rápidamente aplicaciones de demostración para compartir con otras personas que siempre están actualizadas con nuestra base de datos. También la capacidad de programar ejecuciones es muy conveniente. Reseña recopilada por y alojada en G2.com.

Importar paquetes de nuestro propio repositorio privado de GitHub y obtener paquetes de pip está bien, pero no siempre es tan fluido como me gustaría. Además, los paquetes que están disponibles por defecto no siempre están actualizados (tiktoken, por ejemplo). Sería bueno si hubiera alguna otra forma de especificar de manera fluida qué paquetes y qué versiones de paquetes quieres incluir en tu aplicación. Reseña recopilada por y alojada en G2.com.

I absolutely love how I can query from many sources -- my job typically has large CSVs that are unmanageable in Excel / GSheets, and I love how I can query from both our Snowflake source AND these CSVs. It's been a game changer. I can write complex code and have a digestible format for someone at the end. Reseña recopilada por y alojada en G2.com.

I've found that some of the visualization options are a bit limited (can't create totals on a pivot table) Reseña recopilada por y alojada en G2.com.

Hex sigue sorprendiéndome. Simplemente funciona. Es una herramienta poderosa que también es fácil de usar. Cada vez que me pregunto si puedo usar Hex para resolver mi problema, la respuesta es casi siempre positiva. Me encantan sus herramientas de visualización de datos, la velocidad del producto y su asistente de IA. Reseña recopilada por y alojada en G2.com.

Para ser honesto, no he encontrado ninguno. Un par de veces, pensé que sería genial que Hex tuviera características xyz, y poco después el equipo las añadió. Reseña recopilada por y alojada en G2.com.