Creating Data Lakehouse using Amazon S3 and Athena

As organizations accumulate massive amounts of structured and unstructured data, consequently, the need for flexible, scalable, and cost-effective data architectures becomes more important than ever. Moreover, with the increasing complexity of data environments, organizations must prioritize solutions that can adapt and grow. In addition, the demand for real-time insights and seamless integration across platforms further underscores the importance of robust data architecture. As a result, Data Lakehouse — combining the best of data lakes and data warehouses — comes into play. In this blog post, we’ll walk through how to build a serverless, pay-per-query Data Lakehouse using Amazon S3 and Amazon Athena.

What Is a Data Lakehouse?

A Data Lakehouse is a modern architecture that blends the flexibility and scalability of data lakes with the structured querying capabilities and performance of data warehouses.

• Data Lakes (e.g., Amazon S3) allow storing raw, unstructured, semi-structured, or structured data at scale.
• Data Warehouses ...