Low-Latency & High-Concurrency Analytics Over Data Lakes

Explore a 31-minute video presentation from Databricks on achieving low-latency and high-concurrency analytics over data lakes. Discover how Firebolt leverages advanced lake-scale optimized approaches to storage and indexing, enabling efficient analytics on previously unmanageable data volumes. Gain insights into real-world applications and witness a live demonstration showcasing the latest advancements in data warehouse evolution, sparse indexes adapted for cloud environments, and innovative materialized views. Learn about the challenges of low-latency analytics in data lakes and understand how storage and compute optimizations work together to overcome these obstacles. Delve into the concept of aggregating indexes and explore how data warehouses can function as accelerators for data lakes.

Intro
Agenda
A new leap in the evolution of data warehouses
The Firebolt difference
Why low-latency analytics matters
Challenges with low-latency analytics in data lakes
Storage & compute optimized together
What are sparse indexes?
Adapting sparse indexes for the cloud
A new take on materialized views Aggregating Indexes
The DW as a data lake accelerator