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 Zepl:
a side-by-side comparison for 2024
Comparing two data science notebooks.
Zepl
Notebook-powered analytics for enterprise teams.
Amazon Sagemaker
Zepl
Setup
Fully managed (setup in hours)
Fully managed (setup in hours)
Can you self-host?
Can you self-host?
No, you must use a managed offering
No, you must use a managed offering
Features
Is it Jupyter compatible?
Is it Jupyter compatible?
Jupyter-compatible
Unknown
Programming languages
Programming languages
Jupyter languages (e.g. Python, R)
Python
R
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
Unknown
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
Unknown
Notebook scheduling with additional tools
Notebook scheduling is built in
Management
Reproducibility
Reproducibility
There is no support for reproducibility
Environments are reproducible by default
File-based (use Git)
Version history is built in
No support for collaborative editors
Multiple editors at the same time
Comments
Comments
File-based (use GitHub)
Comment on items within a notebook
Notebook organization
Notebook organization
View notebooks in a list
Unknown
Licensing
License
License
Proprietary
Proprietary
Price
Price
Free tier
Pay for compute
Unknown