Databricks Notebooks vs Observable: a side-by-side comparison for 2024
Comparing two data science notebooks.
Databricks Notebooks
Collaborate across engineering, data science, and machine learning teams with support for multiple languages, built-in data visualizations, automatic versioning, and operationalization with jobs.
Make sense of the world with data, together. Explore, visualize, and analyze data. Collaborate with the community. Learn and be inspired. Share insights with the world.
Databricks Notebooks
Observable
Setup
Is it managed?
Is it managed?
Fully managed (setup in minutes)
Fully managed (setup in minutes)
Can you self-host?
Can you self-host?
You can self-host (setup in hours)
No, you must use a managed offering
Features
Is it Jupyter compatible?
Is it Jupyter compatible?
Jupyter-compatible
Not Jupyter-compatible
Programming languages
Programming languages
Jupyter languages (e.g. Python, R)
JS
What kind of data sources can you connect to?
What kind of data sources can you connect to?
Connect with Jupyter libraries (e.g. SQLAlchemy, psycopg2)
Connect to data warehouses (Databricks)
Connect with JS libraries (e.g. REST APIs)
Connect to databases (MySQL, Postgres)
Connect to data warehouses (BigQuery, Snowflake)
Provided file storage
What kind of data visualization can you do?
What kind of data visualization can you do?
Jupyter data visualization (e.g. Matplotlib, Altair, Plotly)