As data volumes continue to grow exponentially, AI inference and big data analytics demand systems that can scale, while providing real-time processing capabilities.

A data lakehouse combines the horizontal scalability of data lakes with the transactional management of a data warehouse. Lakehouses decouple storage from compute, so that compute resources can be scaled on demand and queried by different tools that support open formats.

In combining the data warehouse and the data lake, the lakehouse becomes a new entity, one that includes the warehouse’s transactional layer. This simplified architecture enables greater horsepower and agility for AI, BI, ML, and really, all analytics.

This whitepaper by Supermicro and AMD shows how you can manage ever-growing data volumes while extracting real-time analytics with a data lakehouse. It details how this unified architecture simplifies data management and enhances agility for all your analytics workloads.

Download this whitepaper to discover how data lakehouses can help you:

• Optimize your performance - addressing challenges with managing large data volumes for AI and analytics
• Unify your data, allowing structured, semi-structured, and unstructured data to coexist and be accessed seamlessly
• Offer greater horsepower and agility for various analytical workloads, including AI, BI, and ML