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Run Datasette on AWS as a serverless application:

Sufficiently small databases (unzipped size up to ~250 MB, zipped size up to ~50 MB) will be inlined in the Lambda deployment package. Others will be published to S3 and fetched on Lambda startup.

You can see a demo using Datasette's fixtures db here:

Getting started


Clone the repo and run ./update-stack <stack-name> [flags] <sqlite.db> [<sqlite.db> ...], e.g.:

git clone
cd datasette-lambda
./update-stack northwinds northwinds.db`

Some Datasette flags are supported:

  • --config key:value, to set config options
  • --cors, to enable Access-Control-Allow-Origin: * headers on responses
  • --metadata <metadata.json>, to provide metadata

And some non-Datasette flags are supported:

  • --domain or --domain, if is a hosted zone in Route 53
    • register a CNAME record that points to the CloudFront distribution
    • register an SSL certificate for the domain (you'll have to ack a confirmation email from Amazon)
    • associate that certificate to the CloudFront distribution
  • --prefix some/path, to mount the Datasette app at a path other than the root

A CloudFormation stack will be created (or updated) with an S3 bucket.

The stub code and SQLite database(s) will be uploaded to the S3 bucket.

A second CloudFormation stack will then be created (or updated) with the necessary IAM roles, CloudFront, API Gateway and Lambda entities to expose your Datasette instance to the web.

Watching logs

./tail-logs <stack-name> will watch the CloudWatch logs for the Lambda (NB: not the API Gateway) service - this can be useful for debugging runtime errors in Datasette itself.


Run ./delete-stack <stack-name> to tear down the infrastructure.

Note: AWS has a rough edge with deleting Lambda@Edge functions. You will need to run delete-stack, then wait a period of time, and run it again for the entire stack to be successfully removed. Ref: AWS docs

Known issues / future work

  • Downloads from S3 should use an atomic fetch/rename to be robust against transient errors
  • We should embed the DB in the Lambda package itself, when possible, to avoid the coldstart S3 fetch
  • Repeated calls of update-stack should be robust against template-not-changed errors
  • Fix issue with base_url not always being respected in generated URLs (maybe issue in how we use Mangum?)
  • Be able to host multiple DBs
  • Use the passed-in name of the DB as the DB name
  • Create a CloudFront distribution
  • Optionally be able to use a custom domain name on CloudFront
  • Parity: Support CORS flag
  • Parity: Support metadata flag
  • Parity: Support config options
  • Fix wrong absolute URLs for facets/next page (ds.absolute_url)
  • Use API Gateway's faster/cheaper HTTP APIs instead of REST APIs (requires erm/mangum #94)


  • Be able to customize the "mount" point of the CloudFront distribution
  • Add support into core datasette's publish command, fixing #236


Run Datasette on AWS serverless.








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