Integration · Webhooks and data
RevenueDot writes scheduled exports of transactions, customers, subscriptions and events to your own Amazon S3, Cloudflare R2 or Google Cloud Storage bucket. Files are gzip CSV or Parquet, run daily or weekly, and hold only new and changed rows unless you pick a full export. The run history shows every file, row count and error.
What teams do with it
What RevenueDot sends
transactions, customers, subscriptions and events. Pick any of them per export, and limit them to production, sandbox or both.transactions uses the column names of RevenueCat's transactions export where RevenueDot can fill them: store_transaction_id, product_identifier, start_time, end_time, price_in_usd, refunded_at, is_trial_conversion, is_sandbox and more, plus app_id.<prefix>/<YYYY-MM-DD>/<table>_<YYYYMMDDTHHMMSSZ>.csv.gz (or .csv, .parquet), split into _part2, _part3 and so on above 10,000 rows.YYYY-MM-DD HH:MM:SS. Parquet uses Snappy and typed columns: timestamps, integers, decimals, booleans and JSON.Setup
Amazon S3: an IAM user with s3:PutObject on arn:aws:s3:::<bucket>/* and s3:ListBucket on the bucket. Cloudflare R2: an API token with Object Read & Write. Google Cloud Storage: a service account with Storage Object Creator and Storage Legacy Bucket Reader.
In RevenueDot, open Integrations → Scheduled Data Exports → New export and fill in the destination, bucket, prefix and credentials. For R2, add your Cloudflare account ID. For MinIO or other S3-compatible storage, choose Amazon S3 and fill in Endpoint.
Choose the tables, CSV or Parquet, daily (an hour in UTC) or weekly (a day of the week), and incremental or full. Click Create export.
Click Check bucket. RevenueDot runs an S3 HeadBucket or a GCS bucket lookup and says what to fix on a 403 or 404.
Click Run now for the first export. Later runs follow the schedule, and the run history shows each file, its rows and size, and any error.
| Table | What a row is | Key columns |
|---|---|---|
transactions | One purchase, trial or renewal | rc_original_app_user_id, store_transaction_id, product_identifier, start_time, end_time, price_in_usd, refunded_at, is_sandbox, updated_at |
customers | One customer | rc_original_app_user_id, aliases, first_seen_time, last_seen_time, platform, app_version, country, updated_at |
subscriptions | The current state of one subscription | Store, product, dates, period type, cancellation, billing issue, refund, price, country, updated_at |
events | One event webhooks receive | event_id, type, event_time, recorded_at, environment, app_id, product, store, price, payload (the webhook body as JSON) |
The four exported tables.
| Destination | Credentials | Permissions |
|---|---|---|
| Amazon S3 | Access key ID and secret access key | s3:PutObject on the bucket's objects and s3:ListBucket on the bucket |
| Cloudflare R2 | Cloudflare account ID, R2 access key ID and secret | R2 API token with Object Read & Write on the bucket |
| Google Cloud Storage | Service account JSON key | Storage Object Creator and Storage Legacy Bucket Reader |
| S3-compatible (MinIO and the like) | Access key ID and secret, plus an endpoint | Same as Amazon S3 |
Every dashboard action is an API call under /v2/projects/{project_id}/integrations/exports. This one writes Parquet files of two tables to R2 every day at 03:00 UTC. The secret is sealed with AES-256-GCM and never returned.
curl -s -X POST "$REVENUEDOT_URL/v2/projects/$PROJECT_ID/integrations/exports" \
-H "Authorization: Bearer $SECRET_KEY" -H "Content-Type: application/json" \
-d '{"name":"Warehouse","destination":"r2","config":{"bucket":"revenue-exports","prefix":"revenuedot","account_id":"'"$CF_ACCOUNT_ID"'","access_key_id":"'"$R2_KEY_ID"'"},"credentials":{"secret_access_key":"'"$R2_SECRET"'"},"format":"parquet","schedule":"daily","hour_utc":3,"tables":["transactions","events"]}'A refunded transaction is exported again with price_in_usd set to 0 and refunded_at set. Keep the latest row per store_transaction_id by updated_at, then sum.
SELECT DATE_TRUNC('month', start_time) AS month, SUM(price_in_usd) AS revenue
FROM transactions
WHERE NOT is_sandbox
GROUP BY 1
ORDER BY 1;FAQ
Create a bucket and an IAM user with s3:PutObject and s3:ListBucket. In RevenueDot open Integrations → Scheduled Data Exports → New export, enter the bucket and keys, pick tables, format and schedule, click Check bucket and then Run now.
Yes. RevenueDot writes to Amazon S3, Cloudflare R2 and Google Cloud Storage, and to S3-compatible storage such as MinIO through an endpoint. R2 takes an access key pair plus your Cloudflare account ID. GCS takes a service account JSON key.
Use Parquet if your warehouse reads it, because its columns are typed: timestamps, integers, decimals, booleans and JSON. Use CSV if you load files by hand. CSV is gzip by default, with a header row and UTC times.
Yes. Each run exports rows that changed since the last successful run, including a transaction refunded or reversed in that window. The refunded row has price_in_usd 0 and refunded_at set, so keep the latest row per store_transaction_id by updated_at.
Yes. RevenueDot's transactions table uses the column names of RevenueCat's scheduled data exports that it can fill (checked October 2026), so SQL written against them keeps working. RevenueDot is open source and free to self-host.
Sources: RevenueCat: scheduled data exports · Amazon S3 documentation · Cloudflare R2 documentation · Google Cloud Storage documentation. Scheduled data exports is a trademark of its owner, used to describe compatibility. RevenueDot is not affiliated with or endorsed by it.
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