Amazon Sagemaker
WebsiteAmazon 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 VS Code:
a side-by-side comparison for 2024
Comparing two data science notebooks.
VS Code
WebsiteVisual Studio Code is a lightweight but powerful source code editor. It supports working with Jupyter Notebooks natively, as well as through Python code files.
Amazon Sagemaker
VS Code
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
Jupyter-compatible
Programming languages
Programming languages
Jupyter languages (e.g. Python, R)
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 with Jupyter libraries (e.g. SQLAlchemy, psycopg2)
AWS
Connect with Jupyter libraries (e.g. SQLAlchemy, psycopg2)
What kind of data visualization can you do?
What kind of data visualization can you do?
Jupyter data visualization (e.g. Matplotlib, Altair, Plotly)
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 with additional tools
Notebook scheduling with additional tools
Management
Reproducibility
Reproducibility
There is no support for reproducibility
There is no support for reproducibility
File-based (use Git)
File-based (use Git)
No support for collaborative editors
File-based (use Git)
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 (MIT)
Price
Price
Free tier
Pay for compute
Free