Building a modern lakehouse architecture: Yggdrasil Gaming’s journey from BigQuery to AWS

This article details Yggdrasil Gaming's migration from Google BigQuery to a modern Apache Iceberg-based lakehouse architecture on AWS, implemented with partner GOStack.

• Migrated from multi-cloud setup to unified AWS analytics services reducing operational complexity
• Implemented Apache Iceberg tables on Amazon S3 for ACID transactions and schema evolution
• Deployed Debezium Server for real-time change data capture into Iceberg tables
• Migrated ETL pipelines: Cloud Run functions to AWS Lambda, Dataproc to Amazon EMR
• Rebuilt analytical transformations using dbt with Amazon Athena as query engine
• Consolidated orchestration using Argo Workflows on Amazon EKS
• Enabled AWS Lake Formation for fine-grained row-level access control for multi-tenant model
• Achieved 60% reduction in data processing costs and 75% lower analytics latency

Yggdrasil successfully modernized their data platform using open formats and serverless services, enabling advanced analytics and AI/ML initiatives while significantly reducing costs and operational overhead.