As organizations increasingly adopt data lake architectures, analytics databases face significant integration challenges beyond simple data ingestion. This talk explores the complex technical hurdles encountered when building robust connections between analytics engines and modern data lake formats.

We'll examine critical implementation challenges, including the absence of native library support for formats like Delta Lake, which necessitates expansion into new programming languages such as Rust to achieve optimal performance. The session explores the complexities of managing stateful systems, addressing caching inconsistencies, and reconciling state across distributed environments.

A key focus will be on integrating with external catalogs while maintaining data consistency and performance - a challenge that requires careful architectural decisions around metadata management and query optimization. We'll explore how these technical constraints impact system design and the trade-offs involved in different implementation approaches.

Attendees will gain a practical understanding of the engineering complexity behind seamless data lake integration and actionable approaches to common implementation obstacles.