When importing data into an existing Airtable table, the main challenge is
adding new data without disrupting what’s already there. You need to fit incoming data into an existing structure without breaking field types, overwriting records, or creating duplicates.
The right approach depends on where your data comes from and whether it changes over time. Some sources work well with Airtable’s built-in import tools, while others require a repeatable way to keep an existing table up to date.
This guide walks through the available options, explains when each one makes sense, and helps you choose the right approach based on your data source and update needs.
One-time imports using Airtable’s built-in tools
Airtable provides built-in options for importing data into an existing table. These tools are intended for manual imports and are most useful when you’re bringing data in once rather than keeping it updated over time.
Manual file imports (CSV or Excel)
CSV and Excel files can be imported into an existing table using the Import data option from the table menu.
During the import, Airtable attempts to match columns from the file to existing fields, allowing you to review and adjust mappings before completing the import. The data is added to the table as new records.
Manual Google Sheets imports
Airtable also supports importing data from Google Sheets.
You can connect a Google account, select a spreadsheet and sheet, and map columns to fields in an existing table. The import pulls in the current state of the sheet at the time it runs.
Where one-time imports start to break down
One-time imports work well when data is static, but problems start to appear as
soon as the same data needs to be imported again.
Updating existing records without creating duplicates
When data is imported more than once, Airtable doesn’t automatically know which incoming rows correspond to existing records. Without a clear way to match records, repeated imports often result in duplicate rows rather than updates to existing ones.
This becomes especially noticeable when you’re importing into a table that’s already being used in workflows, views, or automations.
Changes, reordering, and shared source files
Source data rarely stays perfectly consistent. Rows may be reordered, new rows added, or values edited by other people.
With manual imports, even small changes can make it difficult to safely re-import data into the same table without reviewing the results each time.
Repeating imports over time
As soon as imports need to happen regularly — daily, weekly, or on a schedule — manual workflows become time-consuming and error-prone.
At that point, the challenge isn’t getting data into Airtable once, but finding a reliable
way to import updates without constantly redoing the same steps.
Importing data into an existing table automatically
When one-time imports aren’t enough, the alternative is to use a repeatable
import that applies updates to the same Airtable table. This avoids manually re-uploading files or re-running native imports each time the source data changes.
Repeatable imports instead of manual re-uploads
A repeatable import can be run multiple times using the same configuration, making it easier to bring in updated data without recreating fields or reviewing each import from scratch.
This approach works across common data sources, including files, Google Sheets, and APIs.
Updating existing records using a unique field
To update existing records rather than creating duplicates, imports need a way to match incoming rows to records that already exist in Airtable.
Tools like Data Fetcher support this by letting you specify a unique field using Update Based on Field(s), so matching records are updated when the import runs again.
Running imports automatically in the background
Once configured, imports can run automatically on a schedule, allowing updates to be applied without manual steps.
How to import different data types into an existing Airtable table
Once you’re using repeatable imports, the exact setup depends on where your data comes from.
Below is a high-level overview of how common data sources are typically handled, with links to detailed guides for each case.
Import CSV to Existing Airtable table
If your data comes from CSV, importing into an existing table works well
when the file structure is consistent and includes a reliable identifier
for each row.
For files that are updated regularly or generated automatically, importing from a file URL makes it possible to re-run the import without manually uploading new files each time.
→ See the full guide: Import CSV into Airtable
Import Google Sheets to Existing Airtable table
Google Sheets can be imported into an existing table using Airtable’s native import for one-time use.
If the sheet is updated over time, a repeatable import allows the same sheet to be re-imported safely, updating existing records instead of we're this is what creating duplicates.
→ See the full guide: Import Google Sheets into Airtable
Import APIs and feeds (JSON or XML) to Existing Airtable table
Data from APIs and feeds can’t be imported into an existing Airtable table using Airtable’s built-in tools.
These sources require a repeatable import that fetches data directly from the API or feed and maps it into your table structure.
→ See the guides: Import JSON into Airtable and Import XML into Airtable
