Iceberg-First Ingestion: How Taktile cut 70% of costs

Taktile faced a significant challenge when their event data grew 12 times in a year, overwhelming their existing data infrastructure. Initially, their system directed API events through Lambda functions into Snowflake, but this setup couldn't handle the increasing load, resulting in backlogs and inefficient processing. To address this, Taktile introduced Apache Iceberg tables between Lambda and Snowflake, allowing Lambda to manage raw data processing while Snowflake focused on analytics. This separation of concerns enabled more efficient resource allocation, reducing warehouse compute costs by 70%. Additionally, the team optimized their data transformation process by using DuckDB locally for raw data processing, further enhancing performance and cost-effectiveness. Taktile's strategic approach, based on incremental change and leveraging open standards, allowed them to efficiently scale their system without a complete overhaul, providing valuable insights for other teams facing similar challenges.

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