Querybook
Querybook is Pinterest’s open-source big data IDE via a notebook interface.
Querybook vs Amazon Sagemaker:
a side-by-side comparison for 2024
Comparing two data science notebooks.
Amazon Sagemaker
Amazon SageMaker helps data scientists and developers to prepare, build, train, and deploy high-quality machine learning (ML) models quickly by bringing together a broad set of capabilities purpose-built for ML.
Querybook
Amazon Sagemaker
Setup
No, you must host it yourself
Fully managed (setup in hours)
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?
Not Jupyter-compatible
Jupyter-compatible
Programming languages
Programming languages
Python
Jupyter languages (e.g. Python, R)
What kind of data sources can you connect to?
What kind of data sources can you connect to?
Connect to data warehouses (Snowflake, Google BigQuery, etc.)
Connect to databases (PostgreSQL, MySQL, etc.)
Connect with Jupyter libraries (e.g. SQLAlchemy, psycopg2)
AWS
What kind of data visualization can you do?
What kind of data visualization can you do?
UI for building charts
Jupyter data visualization (e.g. Matplotlib, Altair, Plotly)
Reactivity
Reactivity
No reactivity, you decide the execution order
No reactivity, you decide the execution order
Notebook scheduling is built in
Notebook scheduling with additional tools
Management
Reproducibility
Reproducibility
With effort, you can make reproducible environments
There is no support for reproducibility
No version history
File-based (use Git)
Multiple editors at the same time
No support for collaborative editors
Comments
Comments
No support for comments
File-based (use GitHub)
Notebook organization
Notebook organization
Unknown
View notebooks in a list
Licensing
License
License
Open-source (Apache 2.0)
Proprietary
Price
Price
Free
Free tier
Pay for compute