How does the developer experience between Snowflake and Databricks compare?

Summary

• Both platforms give developers a browser editor with notebooks, a CLI, a VS Code extension, Git integration and an AI coding agent.
• The real difference is the programming model: Databricks runs Python, SQL, Scala and R on Apache Spark compute, and Snowflake pairs SQL with Snowpark libraries for Java, Python and Scala that push processing down into Snowflake.
• Databricks lets you run code from a local IDE on Databricks compute through the IDE extension for VS Code and Cursor, Databricks Connect, or the SSH tunnel (Beta).
• Databricks ships projects as code with Declarative Automation Bundles, defined in a databricks.yml file and deployed with the Databricks CLI; Snowflake's CLI (snow) has command groups for SQL, Snowpark, Streamlit, notebooks, Git and dbt.
• Each has a coding agent: Genie Code in the Databricks workspace plus the Genie Code CLI (Beta) in your terminal, and Snowflake CoCo (Cortex Code) in Snowsight, a desktop app and a CLI.

How does the developer experience between Snowflake and Databricks compare?

On a tooling checklist the two platforms now look alike. The difference is the programming model underneath. On Databricks, Apache Spark powers the compute clusters and SQL warehouses, and you write Python, SQL, Scala or R in notebooks or in your own IDE and run it on that compute. Snowflake pairs SQL with Snowpark libraries for Java, Python and Scala, which push data transformations down into Snowflake. For teams that write most of their code in Python and want local IDE workflows and CI/CD on the same compute that runs production, we believe Databricks is a strong fit.

Databricks vs Snowflake: how they compare

Capability	Databricks	Snowflake
Languages	Python, SQL, Scala and R in notebooks	SQL, plus Snowpark libraries for Java, Python and Scala
Browser development	Notebooks with real-time coauthoring, comments and automatic versioning	Workspaces in Snowsight, a unified editor for SQL and Python files; Notebooks in Workspaces is the next generation of Snowflake Notebooks
Local IDE	IDE extension for VS Code and Cursor; a PyCharm plugin built by JetBrains	Snowflake extension for VS Code; Snowpark code can be authored in Jupyter, VS Code or IntelliJ
Running local code on the platform	Databricks Connect (Python, R, Scala) runs Spark code on Databricks compute; the SSH tunnel (Beta) attaches VS Code, Cursor or a terminal to serverless, AI Runtime or classic compute	Snowpark DataFrames run lazily on the server, and need no separate cluster outside Snowflake
Command line	Databricks CLI (databricks)	Snowflake CLI (snow)
Deploy as code	Declarative Automation Bundles describe jobs, pipelines, dashboards, Model Serving endpoints and MLflow assets in databricks.yml; a Terraform provider handles infrastructure	Snowflake CLI command groups for Snowpark, Streamlit, Native Apps, notebooks and dbt
Git	Git folders, a visual Git client and API for cloning, branching, committing and resolving merge conflicts	Git repository clones synced from GitHub, GitLab, Bitbucket, Azure DevOps or AWS CodeCommit, with commit and push from Workspaces, Streamlit apps and notebooks
AI coding agent	Genie Code in notebooks, the SQL editor, the pipeline editor, AI/BI Dashboards and MLflow; Genie Code CLI (Beta) in the terminal	Snowflake CoCo in Snowsight, CoCo Desktop and CoCo CLI, each listed as generally available
Apps and containers	Databricks Apps with Streamlit, Dash, Gradio, React, Angular, Svelte or Express	Streamlit in Snowflake; Snowpark Container Services runs OCI images on compute pools

Both products change quickly: Snowflake is moving users from Legacy Notebooks to Notebooks in Workspaces, and the Databricks SSH tunnel and Genie Code CLI are in Beta. Check current docs before you standardize.

How Databricks approaches developer experience

In the workspace. Notebooks run Python, SQL, Scala and R with real-time coauthoring and automatic versioning. Git folders connect them to your remote repository. Genie Code is the AI coding and data assistant in the workspace: by default it works as an autonomous agent that plans, runs code and fixes errors, and you can ask it to just explain instead.
From your IDE. The Databricks IDE extension connects VS Code or Cursor to a workspace, runs local Python files on remote clusters or serverless compute, and runs files and notebooks as Lakeflow Jobs. Databricks Connect is a client library for the Databricks Runtime that connects IDEs such as VS Code, PyCharm and IntelliJ IDEA to Databricks compute. The SSH tunnel, in Beta, starts with databricks ssh connect --ide vscode. It doesn't use port 22: traffic goes over the same HTTPS endpoint as other Databricks CLI commands, using WebSockets, and the session is authenticated as the user who started it.
In the terminal. The Genie Code CLI, in Beta, starts with genie in a project directory. It reads and edits local files, runs commands and uses the Databricks CLI, including databricks genie ask, to find and query data under your own identity. Model access goes through Unity Gateway.
Shipping to production. Declarative Automation Bundles (formerly Databricks Asset Bundles) put jobs, pipelines, dashboards, serving endpoints and MLflow experiments in source files you review and test like any other code. databricks bundle init starts a project from a template, and bundles deploy from a GitHub CI/CD workflow. The Terraform provider and SDKs for Python, JavaScript, Java, Go and R cover the rest.

FAQs

Can I use VS Code with both Snowflake and Databricks?

Yes. Snowflake has an extension that runs Snowflake SQL in VS Code. Databricks has an IDE extension for VS Code and Cursor, plus Databricks Connect and an SSH tunnel (Beta) for running local code on Databricks compute.

Does Snowflake support Python development?

Yes. Snowpark provides libraries for Java, Python and Scala, and Snowflake Notebooks support Python, SQL and Markdown cells.

Do both platforms have an AI coding agent?

Yes. Databricks has Genie Code in the workspace and the Genie Code CLI (Beta) in the terminal. Snowflake has CoCo, delivered in Snowsight, as a desktop app and as a CLI.

Is the Databricks SSH tunnel generally available?

No. The SSH tunnel is in Beta, and Databricks notes that its cost and pricing are subject to change.