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.
Amazon Sagemaker vs Zeppelin:
a side-by-side comparison for 2024
Comparing two data science notebooks.
Zeppelin
Web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala and more.
Amazon Sagemaker
Zeppelin
Setup
Fully managed (setup in hours)
No, you must host it yourself
Can you self-host?
Can you self-host?
No, you must use a managed offering
You can self-host (setup in hours)
Features
Is it Jupyter compatible?
Is it Jupyter compatible?
Jupyter-compatible
Not Jupyter-compatible
Programming languages
Programming languages
Jupyter languages (e.g. Python, R)
Python
SQL
Spark
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)
AWS
What kind of data visualization can you do?
What kind of data visualization can you do?
Jupyter data visualization (e.g. Matplotlib, Altair, Plotly)
Unknown
Reactivity
Reactivity
No reactivity, you decide the execution order
No reactivity, you decide the execution order
Notebook scheduling with additional tools
Notebook scheduling is built in
Management
Reproducibility
Reproducibility
There is no support for reproducibility
With effort, you can make reproducible environments
File-based (use Git)
File-based (use Git)
No support for collaborative editors
File-based (use Git)
Multiple editors, one at a time (asynchronous)
Comments
Comments
File-based (use GitHub)
File-based (use GitHub)
Notebook organization
Notebook organization
View notebooks in a list
File-based
Licensing
License
License
Proprietary
Open-source (Apache 2.0)
Price
Price
Free tier
Pay for compute
Free