Enabling Multi-Region Data Systems at Notion

Summary

Notion’s data residency work keeps customer data processed and stored in the region where it was generated, supporting EU requirements across Search, analytics, scheduled events, and AI. To make this possible, Notion modularized infrastructure around isolated private networks and workspace IDs, then deployed regional data lakes, Kafka clusters, Spark jobs, Elasticsearch, and vector databases. Debezium captures Postgres changes into regional Kafka, while Airflow remains a centralized orchestration layer that routes jobs to regional EMR clusters; event logging similarly routes traffic by workspace and sanitizes data before Snowflake. Centralized mapping tables, shared region helpers, Terraform, and localized sanitization let teams retain a unified Snowflake environment without exporting customer data. The work took months, and Notion says it is applying these patterns to Japan and South Korea while aiming to provision future regional data stacks within days rather than months.

Takeaways

1. 1

   A centralized mapping table records each workspace’s active region and supports routing, AI onboarding, and data migrations across regions.

2. 2

   Airflow remains in a US datacenter because it does not process customer data directly; regional EMR clusters execute the Spark jobs in the appropriate region.

3. 3

   Event logging moved from a single-region Flink, S3, and Snowpipe design to regional Snowpipe streaming connectors that push sanitized events directly to Snowflake.