Data tables
Overview
Data tables integrate data storage within your n8n environment. Using data tables, you can save, manage, and interact with data directly in your workflows without relying on external database systems for scenarios such as:
Persisting data across workflows in the same project
Storing markers to prevent duplicate runs or control workflow triggers
Reusing prompts or messages across workflows
Storing evaluation data for AI workflows
Storing data generated from workflow executions
Combining data from different sources to enrich your datasets
Creating lookup tables as quick reference points within workflows
Working with data tables
You can create, filter, and manage data tables and their data in three ways: using the Data Table node, the DataTable API endpoint , or the Data tables tab.
Data Table node
Use data tables inside workflows to store and manage data, enabling automated creation, retrieval, updates, and deletions as your workflow runs.
See the Data Table node for full documentation.
DataTable API endpoint
Work with data tables programmatically using the /datatables endpoint in the n8n API.
See the API reference for full documentation.
Data table tab
View and work with data tables directly in the UI through a visual interface. This lets you browse and edit data, and manage tables without building a workflow.
In your n8n project, select the Data tables tab.
Click the split button located in the top right corner and select Create Data table.

Data table creation Enter a descriptive name for your table.
Select how to create the table:
From scratch: Create a new table by manually defining columns and adding rows using the visual interface.
Import CSV: Upload a CSV file to automatically create the table structure and populate it with data from the file.
In the table view that appears, you can:
Rename or delete the data table or its columns
Add and reorder columns to organize your data
Add, delete, and update rows
Edit existing data
Exporting and importing data
From the Data tables tab, you can:
Import CSV data directly into a data table, as described in the previous section
Download a CSV of your data table. Click the three dot menu in the top left and select Download CSV.
Considerations and limitations of data tables
Data tables are suitable for light to moderate data storage. By default, the total storage used by all data tables in an instance is limited to 50MB. In self-hosted environments, you can increase this default size limit using the environment variable
N8N_DATA_TABLES_MAX_SIZE_BYTES.When your data tables approach 80% of your storage limit, n8n displays a warning. A final warning appears when you reach the storage limit. Exceeding this limit will disable manual additions to tables and cause workflow execution errors during attempts to insert or update data.
By default, data tables created within a project are accessible to all team members in that project.
Admins and Owner can see all Users' data tables.
Direct programmatic access to data tables from a Code node isn't supported. You can't access data table values via built-in methods or variables.
Data tables versus variables
Unified tabular view
✓
✗
Row-column relationships
✓
✗
Cross-project access
✗
✓
Individual value display
✗
✓
Optimized for short values
✗
✓
Structured data
✓
✗
Scoped to projects
✓
✗
Use values as expressions
✗
✓
Last updated
Was this helpful?