Amazon SageMaker vs. Observable

The comparison of the two data science notebooks. Both of them are great tools!

The table below summarizes some of the main differences.

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Amazon SageMaker

Logo of 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.

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Logo of Observable

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.

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Amazon SageMaker Observable
License Proprietary Proprietary
Ease of setup Fully managed (but hard) In the browser
Native integrations Within AWS No
Collaboration Shared copies Asynchronous
Versioning Using git No
Reproducibility Problematic Environment, reactivity
Notebooks as products No Interactive applications