Case Study: Intellum achieves scalable data processing with Airbyte

Refining Intellum's Data Processing Systems

Intellum, a pioneer in online learning, needed a more reliable way to unify data from many sources into its Evolve learning platform while meeting strict compliance requirements. Its legacy, home-grown ETL scripts struggled with very large databases, heavy data volumes, and complex incremental syncing, making data ingestion into BigQuery difficult to maintain and scale.

Airbyte helped Intellum break the ETL process into smaller, more manageable steps using API-driven, container-based deployments, prebuilt connectors, and support for CDC and Kubernetes. With Airbyte, Intellum could move around 30 TB of data from more than 17 databases into BigQuery, scale horizontally, and launch the new platform in about two weeks, improving reliability and enabling near real-time data synchronization.

Intellum

Andres Bravo Gorgonio

Software Engineer