Announcing CSV Import: Bring in large datasets to Appwrite with ease_
Learn how to import rows into your Appwrite tables using a simple CSV file, a new feature built on top of Appwrite's migration APIs.
We're introducing a new way to populate your Appwrite databases: row imports from CSV files.
Built on top of Appwrite's migration APIs, this feature makes it easy to bring in large datasets, seed tables, or migrate structured data using only a CSV file.
The CSV row import is useful for migrating user data from external systems, importing inventory records, seeding test environments, or onboarding structured content such as FAQs.
How it works
To get started, create a table and define its columns in the Appwrite Console. Your CSV file should follow a standard format:
- The first row must be a header containing column names that match your table
- Each subsequent row represents a row, with values separated by commas
All required columns must be present in the CSV, and Appwrite will validate each row before importing it.
For example, if your table contains columns like title, author, year, and available, a valid CSV file would look like this:
$id,title,author,year,available
f3k91x8b2q,Harry Potter and the Sorcerer's Stone,J.K. Rowling,1997,true
mz7lq3dp5c,The Fellowship of the Ring,J.R.R. Tolkien,1954,true
x0v4p8ncq2,To Kill a Mockingbird,Harper Lee,1960,false
kq9nmv13ru,The Great Gatsby,F. Scott Fitzgerald,1925,true
p8lw39xsd1,Catch-22,Joseph Heller,1961,true
v42cj0quxp,Pride and Prejudice,Jane Austen,1813,true
Uploading your CSV file
You can upload a new file during import or select an existing one from your project's storage bucket. The Console provides a guided interface to help you select the CSV and link it to your target table. Once uploaded, the import process begins immediately.
Designed for scale
CSV imports are built to scale seamlessly with your data. Whether you're working with a small dataset or importing production-grade records, the system is designed to handle high volumes reliably and efficiently.
The import system performs per-row validation and runs as a background task, allowing it to handle large files efficiently. This ensures reliable performance across a range of scenarios, from lightweight configuration data to large-scale production imports.
Availability and resources
CSV imports are now available on Appwrite Cloud and in the latest self-hosted release.
To learn more, check out the official documentation. If you have any questions or feedback, we'd love to hear from you in the Appwrite Discord community.
Further reading
Create a table with the columns you want, then upload a CSV file whose first row contains matching column names. You can upload a new file during import or pick an existing one from your storage bucket. Appwrite validates each row before importing and runs the job in the background.
Yes, include an optional $id column in the CSV and Appwrite will use those values as row IDs. If you omit the column, Appwrite generates unique IDs automatically. Custom IDs are useful when migrating from another system that already has stable identifiers.
The first row must be a header containing column names that exactly match your table's columns. Each subsequent row represents a row, with values separated by commas. All required columns must be present, or the row will fail validation.
The CSV import system runs as a background task and performs per-row validation, so it can handle production-scale files without blocking the Console. Built on top of Appwrite's migration APIs, it's designed for reliability across both small datasets and large imports.
Appwrite validates each row before importing it, so invalid rows are flagged and skipped rather than corrupting your table. Common causes are missing required columns, type mismatches, or values that violate length or enum constraints. Fix the source CSV and re-run the import for those rows.
CSV imports are useful for migrating user data from external systems, importing inventory records, seeding test environments, and onboarding structured content like FAQs or product catalogs. They're also handy when prototyping with realistic data from spreadsheets or third-party tools.
