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Available on request — The Autumn Lakehouse is provisioned per customer. Contact us at hey@useautumn.com to get access.
The Autumn Lakehouse mirrors your entire Autumn dataset — customers, plans, subscriptions, invoices, balances, events, and more — into your own data warehouse as Apache Iceberg tables. You read it directly with ClickHouse, no API pagination required. It’s built for analytics: BI dashboards, revenue and usage reporting, cohort analysis, and joining Autumn’s billing data against your own product data — all in SQL, against the full history. Every object is delivered as a table named v2_3_<object> (for example v2_3_customers, v2_3_subscriptions, v2_3_events) inside a namespace Autumn assigns you.

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How it works

Autumn’s pipeline continuously reshapes the live billing database into these analytics-friendly tables and syncs them to Iceberg in object storage. You attach your query engine to the catalog once — after that, data keeps flowing in and new columns appear automatically.

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Data freshness

State tables (everything except events) sync under normal load within ~5 minutes of a change in Autumn.
Events have a variable lead time. On initial connection, historical events backfill and can take a while to fully populate — counts will climb until the backfill catches up, then track in near real-time.

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Schema versioning

The v2_3 in every table name is the schema version. The Lakehouse schema changes far less often than Autumn’s main API, and all schema updates are applied automatically — you never run a migration. There are two kinds of change:
  • In-version (additive) — a new column added to an existing v2_3_* table. Your existing saved queries keep working unchanged; the new column simply becomes available.
  • New version — a future v2_4_*. This arrives as a new table and is opt-in. Your existing v2_3_* queries keep working untouched, and you adopt the new shape only when you choose to.
When we foresee a new version, we contact tenants beforehand. You never need to reconnect to receive updates — new columns and tables appear in your existing catalog automatically.

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Next steps

Connecting

Attach ClickHouse to your catalog.

Schema Reference

Every table and column, with the keys to join on.

Querying

Examples, cross-database joins, and footguns to avoid.