IDUG Brazil 2026

•Strategic investments in AI-powered capabilities and operational intelligence
•Hybrid cloud deployment patterns and platform modernization initiatives
•Enhancements focused on developer productivity, automation, and observability
•Performance and resiliency innovations for enterprise workloads
•The long-term product direction and priorities shaping future Db2 LUW releases

Reducing a 500TB database to 60TB introduced a series of significant challenges. This case study details the technical journey to stabilize an environment that struggled with prohibitive recovery windows and the impossibility of performing traditional backups due to its massive volume. The presentation focuses on the end to end reduction effort, including the in-house development of an orchestrator designed to manage large scale workloads while maintaining full control and historical tracking of all operations within the Db2 ecosystem. Participants will see how this transformation of a critical, high volume environment was achieved and how the team sustained an agile, well-governed operation through intelligent automation.

Join us for a deep dive into the latest innovations shaping the continued evolution of Db2 Cloud Services across leading cloud platforms. This session explores recent advancements in Db2 SaaS, AWS Amazon RDS for Db2, and Db2 as a Service on Microsoft Azure as well as Google Cloud.  You’ll learn how these offerings enable flexible deployment choices while meeting demanding enterprise requirements. Whether your focus is efficient application development, optimization, regulatory compliance, cloud strategy, availability, or feature adoption, this session will demonstrate how Db2 Cloud Services are designed to adapt to your needs—providing enterprise-grade reliability, scalability, and flexibility.

The AI problems landing on the desks of DBAs and application developers this year don't all need the same model. Some call for a Large Language Model. Others need a forecasting model, a clustering algorithm, or an embedding model. Plenty can be solved by predictive techniques that have been working quietly for years. One drawer of the toolbox has been getting all the attention. The skill that matters most, knowing which tool fits the problem, has gone quiet. If your data lives in Db2, much of the toolbox is already there.

This session lays the toolbox out on the table. Two axes, what data you have and whether you have labels, organize the AI landscape into a 2×2 you can hold in your head: predictive and unsupervised models for structured data, the same for unstructured data, plus embeddings and generative AI.

Then we map every drawer to a Db2 capability you can use today. In-database machine learning for classification, regression, and clustering. Native vector storage and similarity search. Built-in integration with external embedding and language models. Python frameworks for retrieval-augmented applications and AI agents. We close with production patterns we've seen ship, across the full range of model types and use cases.

Whether you live in SQL or Python, you'll leave knowing which tool to reach for, and where to start.

Join this expert panel for an open Q&A with leading Db2 LUW specialists. Panelists will take on as many attendee questions as time allows, offering practical insights drawn from real customer scenarios and current product capabilities. This interactive session is a chance to deepen your technical understanding, hear expert perspectives, and connect with peers across the Db2 community. Bring your questions and be ready for a lively, knowledge rich-discussion.