Event Warehouse

Write collected events to your data warehouse for long-term storage and analysis.

Overview

The event warehouse writer automatically writes incoming events to a dedicated table in your data warehouse. This gives you a queryable event history alongside your other customer data.

Configuration

Navigate to Events > Warehouse
Select a source (warehouse connection)
Configure the target schema and table name
Click Save

Table Schema

Events are written with the following columns:

Column	Type	Description
`event_id`	string	Unique event identifier
`type`	string	Event type (track, identify, page, group)
`event`	string	Event name (for track events)
`user_id`	string	User identifier
`anonymous_id`	string	Anonymous identifier
`properties`	JSON	Event properties
`traits`	JSON	User traits (for identify events)
`context`	JSON	Event context (IP, user agent, etc.)
`timestamp`	timestamp	Event timestamp
`received_at`	timestamp	When SignalSmith received the event
`write_key_id`	string	Which write key sent the event

Schema Evolution

When new event types or properties appear:

New columns are not automatically added (schema is fixed)
New properties are stored in the properties JSON column
Query JSON columns using your warehouse’s JSON functions

Partitioning

Events are partitioned by date for efficient querying:

BigQuery — Partitioned by received_at date
Snowflake — Clustered by received_at
Databricks — Partitioned by received_at date

API Reference

See Events API for warehouse configuration endpoints.

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