Data Pipelines

Capture every event for your data warehouse.

Every webhook event is a data point. GetHook persists all events durably and fans out to your data warehouse, BI tool, and streaming pipeline simultaneously — with replay for backfills.

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Up and running in minutes
99.9% uptime SLA
Any Business Event
User Events
Payment Events
System Events
every event captured · zero loss
GetHook
persist · replay · fan-out
Fan-out targets
Snowflake / BigQuery
Kafka / Redpanda stream
Looker / Metabase BI
ML feature pipeline
Data Warehouse
Event Stream
BI Tool
ML Pipeline
The problem

Why raw webhooks aren't enough.

The HTTP webhook protocol has no persistence, no retries, and no observability — and it shows.

Events lost before reaching the data warehouse

Your Snowflake loader is down for maintenance. Stripe sends a batch of payment.succeeded events. They fail delivery and are never retried. Your revenue dashboard shows a gap that takes a week to investigate.

Adding a new data destination requires replay

You add Looker next to your existing Metabase. Looker needs the last 90 days of order events to build its first dashboard. Without event persistence and replay, you have to re-export from your transactional database — an expensive, error-prone operation.

Fan-out to multiple sinks requires custom code

Your order events need to reach Snowflake, Kafka, and your ML feature store simultaneously. Writing that fan-out in application code tightly couples your order service to your data infrastructure.

How it works

Three steps to reliable data pipelines webhooks.

From raw HTTP POST to guaranteed delivery — set up in under 10 minutes.

01

Capture all events at ingest

Every event POSTed to GetHook is persisted immediately to Postgres before the 200 OK is returned. Zero data loss guarantee — events are never dropped at ingest time.

terminal
POST /ingest/src_data_capture_token
{ "event_type": "order.completed", "payload": { "order_id": "ord_123", "revenue": 9900, "currency": "usd", "customer_id": "cust_abc" } }
02

Fan-out to all data sinks

Add destinations for Snowflake, Kafka, BigQuery, and your BI tool. Create a route per destination. Each gets independent retry — a slow data warehouse doesn't affect real-time streaming.

terminal
POST /v1/routes
{ "event_type_pattern": "*", "destination_id": "dest_snowflake" }
{ "event_type_pattern": "*", "destination_id": "dest_kafka" }
{ "event_type_pattern": "order.*", "destination_id": "dest_ml_pipeline" }
03

Replay for backfills

Added a new data destination? Replay all historical events to backfill it. Filter by event type and time range to replay only what's needed.

terminal
# Replay all order events from the last 90 days
GET /v1/events?event_type=order.*&from=2024-01-01
# For each event:
POST /v1/events/{id}/replay
Benefits

Everything you need for data pipelines.

Zero-loss event capture

Events are persisted to Postgres before the HTTP 200 is returned. They cannot be lost by destination failures.

Fan-out to all data sinks

One event reaches Snowflake, Kafka, BI tools, and ML pipelines simultaneously — with independent retry per sink.

Replay for backfills

Add a new data destination and replay 90 days of historical events to populate it. No re-exporting from your transactional database.

Filter by event type and time

Query the event store by event type, time range, source, and status. Precise backfills without replaying irrelevant events.

Independent retry per destination

A slow Snowflake loader doesn't block Kafka delivery. Each destination retries independently on its own schedule.

Complete event payload storage

Full event payloads are stored at ingest time. Your data warehouse receives the exact same payload that was originally sent.

Start for free

Ready to stop losing webhooks?

Up and running in minutes. No credit card required. Connect your first source and see events flowing in real time.

No credit card
99.9% uptime SLA
HMAC signatures
AES-256 encryption