Hex + Snowflake: Notebooks in the Cloud

As Snowflake users ourselves, we at Hex have benefited first hand from the power and simplicity Snowflake offers. It powers all of our internal Hex notebooks and is the most used cloud data platform across our customer base.

Today, we're excited to announce earning Elite Partner Status with Snowflake for the comprehensiveness of our integration and our large number of joint customers. We’re highlighting how our extensive integration helps data teams work with large amounts of data in a notebook fast!

💜 Hex + Snowflake partner to make notebooks faster

Snowflake brought workloads and applications into the cloud, Hex brought notebook into the cloud. And together we allow any data team to query infinitely-sized data with SQL or with Python or… with both.

Faster SQL

In traditional notebooks, you are limited to the amount of data a kernel (the core program) can process at one time. Without Snowflake, running a large SQL query can take a long time. In Hex, you can keep almost all of your data in Snowflake while continuing to work with it in the notebook. Because you’re not copying data across the internet, you’re saving significant time—especially with large datasets.

This allows you to process as much data as you like without being constrained by the kernel’s capacity or speed. This means much faster workflows with SQL in a notebook, thanks to using Snowflake as the engine.

Faster Python

When data gets large or data transformations get complex, it is best to use python instead of SQL. Hex has built-in support for Snowflake’s Snowpark for Python API, which lets users write familiar Python code in Hex, but execute it natively *in Snowflake* instead of the kernel.

This takes advantage of the massive scalability and distributed compute of the Data Cloud,  again enabling much faster workflows, but this time using Python and data frames end to end.

Faster SQL & Python Together

In a Hex notebook you can push both SQL queries and Python transformations down to Snowflake to make large data analyses run even faster. Query large data sets, then store them directly as a Snowpark dataframe. This makes jumping directly into large transformations or model training easy.

🧬 Any language, Any amount of data

Many shared customers are now able to work with more data quickly thanks to Hex and Snowflake’s integrations, including Notion and Opensea.

Our customers need tools with low overhead but still flexible enough to handle anything from exploratory analysis to complex data science workflows. Hex and Snowflake are the perfect fits because they work right out of the box and can scale infinitely with almost no setup or maintenance.

“Snowflake opens the Data Cloud to a wider audience, which aligns with our use of Hex as a self-serve analytics environment supporting users ranging from our marketing team to seasoned data scientists. Hex and Snowflake together will help us truly democratize data for users across the business." - Abhiskeh Modi, Software Engineer @ Notion

“Hex is a core component of our modern data stack, supporting exploratory analysis, model prototyping, and hosting internal data-powered tools. Our ability to do work in Python and also write SQL against a dataframe in Hex that reads and writes directly from Snowflake is really key to helping us productionalize our work.” - Jerry Shen, Head of Data @ Opensea

In summary

The first-class integration between Hex and Snowflake allows for a flexible, more in depth analytics process, which allows analysts and data scientists to work faster and deliver better insights to the business. We’re not stopping anytime soon, we’ll be sharing more about our integration roadmap at Snowflake Summit this summer.

If you want to be elite too, join our crew.