Databricks — three new exports for events, system events, and audience changes

The Databricks integration now ships three new export workflows — Export Event Data, Export System Events, and Export Audience Changes — bringing it to parity with the Snowflake and BigQuery destinations. If Databricks is where your team already does analytics, modeling, or BI, you can now keep raw Lytics activity right alongside the rest of your lakehouse data.

What's new

Export Event Data — land raw events from your Lytics data streams in Databricks so analysts and data scientists can query behavioral data with the same SQL and notebooks they use for everything else. Use it to power custom dashboards, train models on first-party signals, or join event history with warehouse data Lytics doesn't see.
Export System Events — pipe Lytics audit-log activity (jobs run, authorizations changed, audiences edited, and more) into Databricks for governance, compliance reporting, and operational monitoring. Scope an export to a single work, segment, or account to feed a focused alerting or oversight workflow.
Export Audience Changes — stream near-real-time enter/exit events for up to ten audiences into Databricks as they happen, with an optional one-time backfill of existing members. Use it to drive downstream activation, attribution analysis, or lifecycle modeling without polling segment membership.

How it works

All three workflows reuse your existing Databricks Database Authorization and load data with COPY INTO against a Databricks Delta table — no new auth method, storage integration, or warehouse setup beyond what you already use for Databricks jobs. Loads are append-only and safe to retry.

See Databricks → Export Event Data, Export System Events, and Export Audience Changes for the full configuration walkthroughs.