How do I send webhooks to BigQuery?

Create a Webhook Relay bucket, attach a function that uses the built-in BigQuery package with a service-account key, and map the incoming payload to your table's columns. Point your provider at the Webhook Relay URL and every webhook is inserted into BigQuery as a row using the streaming insert API — no separate pipeline.

Do I need a data pipeline or Dataflow job?

No. Webhook Relay functions call BigQuery's streaming insert directly from the function that runs on each webhook, so events land in your table in near real time without Pub/Sub, Dataflow or a server in between.

How do I map webhook fields to BigQuery columns?

Inside the function, decode the incoming JSON and build a row object whose keys match your BigQuery table schema, then call the BigQuery insert helper with your project, dataset and table. You control exactly which fields are stored and how they are typed.

Send a Webhook to BigQuery: Stream Events Into a Table

You want every webhook — payments, signups, deploys, alerts — to land in Google BigQuery as a row so you can query and dashboard it. The usual way is to stand up Pub/Sub plus a Dataflow job or a small server to receive the webhook and call the BigQuery API. That's a lot of moving parts for "insert a row."

Webhook Relay does it with a function: it receives the webhook at a stable public URL and inserts the event straight into BigQuery using the streaming insert API — no pipeline, no server.

How it works

Webhook Relay runs a small function on each incoming webhook. The built-in BigQuery package authenticates with a service-account key and streams rows into your table:

Provider --> Webhook Relay bucket --> BigQuery function --> your_dataset.your_table

It runs alongside normal delivery, so you can forward the webhook to your app and insert it into BigQuery at the same time.

1. Prepare BigQuery

Create a dataset and a table whose schema matches the fields you want to store (e.g. event STRING, id STRING, amount NUMERIC, received_at TIMESTAMP).
Create a service account with the roles/bigquery.dataEditor role and download its JSON key.

2. Add the BigQuery function

Create a bucket with a public input and attach a function that maps the payload to a row and inserts it. The full, copy-pasteable example is in the docs: insert and stream data into BigQuery and the BigQuery functions reference.

local body = json.decode(r.RequestBody)

local row = {
  event = body.event,
  id = body.id,
  amount = body.amount,
  received_at = os.date("!%Y-%m-%dT%H:%M:%SZ")
}

bigquery.insert("your-project", "your_dataset", "your_table", row)

3. Point your provider at the URL and test

Use the bucket's public Webhook Relay endpoint as the webhook URL in your provider, then fire a test event:

curl -X POST https://your-webhook-relay-endpoint \
  -H 'Content-Type: application/json' \
  -d '{"event":"invoice.paid","id":"in_123","amount":19.99}'

Query your table a few seconds later and the row is there.

Why stream webhooks into BigQuery

Real-time analytics. Dashboard payments, signups or deploys without waiting for a nightly batch.
No pipeline to maintain. Skip Pub/Sub + Dataflow for simple inserts.
One source, many uses. Forward to your app, archive to GCS, and stream to BigQuery from the same webhook.

Going further

Archive the raw payload to Google Cloud Storage or Amazon S3 alongside the insert.
Transform or filter events before they reach the table.
Fan a single event out to multiple destinations.

Inspect a webhook first or create a free account to start streaming into BigQuery.

Tunnels

Webhooks

User Management