Data lake vs. data warehouse: Why AWS customers are transitioning to data lakes

Mehul Shah, GM for AWS Lake Formation and AWS Glue, explains what data lakes are, the challenges of data lakes, and how technology can help.

Today, tens of thousands of customers are building data lakes on Amazon S3 to break down data silos, centralize all their data assets, and unlock the potential of their data company-wide.

The evolution of data warehousing | Data lakes with AWS Lake Formation | Amazon Science
Mehul Shah describes some of the key technologies that enable data lake advances, and dives into research opportunities for the database community.

During the International Conference on Very Large Databases (VLDB), Mehul Shah, GM for AWS Lake Formation and AWS Glue, gave a talk (above) on why customers are transitioning from monolithic enterprise data warehouses to disaggregated data lake architectures on the cloud. The talk describes the challenges customers face in building, securing, and managing data lakes and how AWS Lake Formation helps solve these problems. Lake Formation makes data ingestion, data cleaning, data security, and data governance simpler, so customer can build data lakes in days instead of months.

Related content

GB, MLN, Edinburgh
We’re looking for a Machine Learning Scientist in the Personalization team for our Edinburgh office experienced in generative AI and large models. You will be responsible for developing and disseminating customer-facing personalized recommendation models. This is a hands-on role with global impact working with a team of world-class engineers and scientists across the Edinburgh offices and wider organization. You will lead the design of machine learning models that scale to very large quantities of data, and serve high-scale low-latency recommendations to all customers worldwide. You will embody scientific rigor, designing and executing experiments to demonstrate the technical efficacy and business value of your methods. You will work alongside aRead more