Your AWS Notebook, connect directly to Athena, Redshift, S3, and more.
With Amazon S3, you can easily store any object in the cloud.
When connected to a Deepnote notebook, your S3 bucket will be mounted along with the notebook's filesystem. Then you can easily reference, upload, delete, or update any files that live in the bucket. S3 can be used to store large data sets that will serve as inputs to your data analysis or model training, or as well as directly save the outputs of your work.
Explore Amazon S3 docs →
Amazon Redshift and Athena are enterprise-ready data warehousing and query solutions that let you separate your compute from storage.
When connected to a Deepnote notebook, you can read, update, or delete any data from Amazon Redshift and Athena directly with SQL queries. The query result can be saved as a DataFrame and later analyzed or transformed in Python, as well as plotted with Deepnote's visualization blocks without writing any code.
Explore Amazon Redshift docs →Explore Amazon Athena docs →
Amazon Elastic Container Registry helps you store, share, and deploy container software anywhere.
Import container images hosted in Amazon Elastic Container Registry to customize your Deepnote environment and add libraries and binaries.
Explore Amazon ECR docs →Security gets better and easier with Deepnote. Stop exporting CSVs and taking screenshots of sensitive data. With Deepnote, you have complete control over data access and security.
Learn more about how data teams using AWS build better data products with Deepnote.
"I knew I’d made the right decision when I started getting feedback from data scientists about how delightful their user experience was."
"We moved over to Deepnote ... we’re no longer copying and pasting screenshots from external sources."
“Our team can conduct analyses in the language most comfortable for them, which makes it accessible to and powerful for everyone.”
Deepnote is proud to be a validated AWS partner.