Warehouse and data lakehouses are converging and Db2 is ready for this shift. Db2 Datalake tables enable access to open-format data stored on remote object storage directly from within the relational database, eliminating the need for complex ETL pipelines or data duplication. This session explores the technical architecture supporting both Hive (ODF) and Iceberg table formats, demonstrating how organizations can query PARQUET, ORC, AVRO, and TEXTFILE data alongside traditional Db2 tables in complex SQL queries while maintaining ACID properties where needed. Attendees will learn implementation strategies for converged warehouse architectures, performance optimization techniques, and real-world use cases where Datalake tables provide bidirectional data flow between relational databases and data lake / lakehouses.
This session is about deep dive technical details of how Z data is integrated with other platforms and solutions. This is an architectural, use case and product level technical session. There will be latest news from the zSW Development and Product Management in the context of Data Management, focused on Db2 for z/OS. The goal of this session is
What are data modernization Challenges – Past, Present, Future IBM Z Data and AI Enterprise Architecture Architectural alternatives to provide Db2 for z/OS data into other platforms for data modernization story Core Products, Virtualization, Data Integration and AI Techniques Replicate, Direct Access, Virtualization – Pros & Cons. Technical and Business Use Cases with Capabilities Roadmaps and Future direction of IBM
Cüneyt Göksu is an Executive IT Specialist for IBM® Z solutions in the context of Data and AI in IBM Germany Development Lab as a member of Center of Excellence team. He holds MBA, Bachelor’s degree and PhD in Computer Science. He has been working with Db2 for z/OS and IBM Z... Read More →
