The comparison of the two data science notebooks. Both of them are great tools!
The table below summarizes some of the main differences.
See all notebooksAmazon 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.
Read moreCollaborative SQL Notebooks. A better way for data teams to analyze, unite & deliver.
Read more– | Amazon SageMaker | Query.me |
---|---|---|
License | Proprietary | Proprietary |
Ease of setup | Fully managed (but hard) | Fully managed |
Native integrations | Within AWS | SQL databases |
Collaboration | Shared copies | Asynchrounous |
Comments | No | No |
Versioning | Using git | No |
Reproducibility | Problematic | OK (only SQL) |
Notebooks as products | No | Public notebooks, shared reports |