Enterprises today struggle with the complexity of simultaneously maintaining data lakes and data warehouses. They grapple with data silos that prevent a single source of truth, the expense of maintaining complicated data pipelines, and reduced decision-making speed.
The answer to this complexity is the lakehouse, a platform architecture that implements data structures and data management features similar to those in a data warehouse, but directly on the low-cost, flexible storage used for cloud data lakes. This new, simplified architecture allows traditional analytics and data science to coexist in the same system.
Register to explore the evolution of data management and to look at the Databricks Lakehouse Platform, a new architecture that combines the best elements of data warehouses and data lakes.
By registering, you’ll gain access to free content about all things Lakehouse — curated for you on one page, including:
Data Lakehouse vs Data Warehouses
Hear Databricks Co-founder and CEO Ali Ghodsi as he discusses why data warehouses and data lakes weren’t designed for today’s use cases, and how the lakehouse builds on these technologies to better unlock the potential of your data.
Customer Talk : Building the Lakehouse at Atlassian
Rohan Dhupelia of Atlassian talks about the evolution of the company’s internal data architecture to the lakehouse as the “sweet spot” between the data warehouse and the data lake.
Free Training: How to Build a Lakehouse
In this technical training, we’ll explore how to use Apache SparkTM, Delta Lake and other open source technologies to build a better lakehouse. This virtual session will include concepts, architectures and demos.
Data Management: The Good, the Bad, the Ugly
Discover how Delta Lake simplifies data management — from data processing with ETL to data governance — and why that makes the lakehouse architecture a reality.