Migrating from Hadoop to an Iceberg-Powered Lakehouse
When organizations began to collect large volumes of data, Hadoop was the backbone of big data workloads. But today’s AI and modern analytics demand agility, speed, and efficiency, qualities Hadoop struggles to deliver.
Modern workloads require modern architectures.
For an AI-ready infrastructure, you need a data lakehouse powered by high-performance object storage. Data lakehouses are built to handle AI tasks such as model creation, training, inference, and generative AI. At the same time, they can also handle traditional data workflows like ad hoc analysis, analytics, and BI.
But saying you need to modernize your infrastructure is the easy part. How do you move forward? Download this guide for a pathway to success that takes you off of Hadoop and sets you on the road to successful AI.