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Start by exporting the content you want to migrate
Notion allows you to export individual pages (with their sub-pages) or your entire workspace
On the Notion desktop or web app:
Open the menu (click the ... in the top-right of a page) and choose Export
Select HTML format (with sub-pages and all content) for a complete backup
To export the entire workspace:
Go to Settings → Workspace → Export all workspace content (workspace owners only)
Make sure to include sub-pages and all content (files, images, etc.)
Notion will compile your data and provide a .zip file for download (large exports might be emailed to you)
Save the exported .zip file to your computer
Unzip it to a convenient folder
The Notion export will contain:
Pages as files (HTML or Markdown)
Subfolders for embedded images or attachments
After extraction:
Verify the folder structure is intact
Check that you can open the main HTML file to navigate your notes offline
This ensures the export is complete and organized correctly
Navigate to the AWS Management Console
Sign in with your AWS credentials
Go to the S3 (Simple Storage Service) section:
Find it under "Storage" services or via the search bar
This will take you to the S3 dashboard where you can manage storage buckets
In the S3 console, click the Create bucket button
Provide a unique name for the bucket (must be globally unique across AWS)
Example: my-notion-backup-2025
Choose an AWS Region (typically one close to you or required by compliance needs)
Leave most settings at their defaults
Ensure "Block all public access" remains enabled (best practice for keeping your bucket private)
Click Create bucket
You should see your new bucket in the list of S3 buckets once created
Click on the name of the new bucket to open it
If you prefer to group your Notion data in folders:
Click Create folder
Name it "NotionExport" or similar
This step is optional:
You may upload files directly to the bucket's root
You can drag-and-drop your entire export folder, which preserves internal folders automatically
In your S3 bucket, click the Upload button
In the upload dialog:
Drag and drop the entire folder containing your extracted Notion data, or
Use the Add files / Add folder buttons to select files and folders manually
Ensure all subfolders (for images, sub-pages, etc.) are included
Click Upload at the bottom of the dialog to begin the transfer
Optional: Enable Bucket Versioning before uploading (recommended for backups)
The console will show progress and display a success message when complete
After upload completion, verify all files and folders are present in the S3 bucket
You should see the same folder names and file names as in your extracted export
To check file integrity:
Select one of the files (e.g., index.html)
Use the Download or Open option in the Actions menu
Open the downloaded file on your computer
Confirm the content displays as expected
By default, uploaded files are private (only you and authorized AWS users can access them)
Ensure you haven't made objects public unintentionally
For sensitive or personal data, keep these default settings
If sharing content or hosting as a static website:
Adjust permissions carefully (disable block public access, set specific objects to public)
Enable static website hosting if needed
Only do this for content you intend to be public
Consider enabling additional features for data durability and security:
Enable bucket versioning via the bucket Properties tab
Versioning keeps previous versions when objects are overwritten or deleted
Encryption:
S3 automatically applies server-side encryption with AWS-managed keys (SSE-S3)
Verify this in object properties (encryption details)
For stricter requirements, configure a bucket-level default encryption policy
With versioning, encryption, and blocked public access, your Notion data backup is safely stored
FAQs
What is ETL?
ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.
Notion is an all-in-one workspace that allows users to organize their personal and professional lives in one place. It combines features of note-taking apps, project management tools, and databases to create a customizable and flexible platform. Users can create pages, databases, and boards to manage tasks, projects, and information. Notion also offers a variety of templates and integrations with other apps to enhance productivity. Its user-friendly interface and collaborative features make it a popular choice for individuals and teams looking to streamline their workflows and stay organized.
Notion's API provides access to a wide range of data types, including:
1. Pages: This includes all the pages in a Notion workspace, including their properties and content.
2. Databases: Notion's databases are a powerful way to organize and manage data. The API provides access to all the databases in a workspace, including their properties and content.
3. Blocks: Notion's blocks are the building blocks of pages and databases. The API provides access to all the blocks in a workspace, including their content and properties.
4. Users: Notion's API provides access to information about the users in a workspace, including their name, email address, and profile picture.
5. Workspaces: The API provides access to information about the workspaces themselves, including their name and ID.
6. Integrations: Notion's API allows developers to create integrations with other tools and services, such as Slack or Zapier.
Overall, Notion's API provides a comprehensive set of tools for accessing and manipulating data within a workspace, making it a powerful platform for building custom applications and workflows.
What is ELT?
ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.
Difference between ETL and ELT?
ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
