IDUG Brazil 2026

The access path chosen by Db2 has a major impact on SQL performance and overall application efficiency. This session offers a quick refresher on access path fundamentals and focuses on best practices for managing access paths across the application lifecycle to ensure stable workload performance. Discover key strategies to keep your applications running smoothly and efficiently.

Introducing SQL Data Insights Pro, generally available since March 2026. This session begins with an introduction to SQL Data Insights, first delivered with Db2 for z/OS 13, followed by an overview of subsequent enhancements that have expanded its capabilities. The session then explores the latest advancements in SQL Data Insights Pro, including support for unstructured data stored in character columns and incremental training to improve model efficiency and scalability. Each feature will be demonstrated using sample data and AI queries, helping attendees understand how these capabilities work in practice. Attendees will gain practical insights into these new capabilities and learn how to leverage them to extract greater value from their Db2 data.

Db2 Connect JCC 12.1.4 now propagates W3C Trace Context to Db2 for z/OS using new DRDA code points (OTLTRCCTX) so z/OS OpenTelemetry spans can be stitched into end-to-end traces. This session dives into the driver implementation, UOW boundary rules, sysplex optimizations, troubleshooting, and our roadmap to bring the same behavior to CLI, .NET, and open-source Db2 drivers.

High Performance DBATs (HP DBATS) is a very important performance feature of Db2 10 for DDF workloads. If applied and used intelligently this feature can generate significant savings in CPU resource consumption. This session will cover the following topics: what is a connection?; What is a DBAT (THREAD)?; thread (DBAT) pooling and DRDA inactive connections; what are High Performance DBATs; good candidate application workloads for High Performance DBATs; gerneral guidance for configuring High Performance DBATs; performance metrics and monitoring; WLM and High Performance DBATs; Issues, Summary.

Db2 enables developers to write Procedures, Functions, and Triggers using SQL PL (SQL Procedure Language). While IBM does provide a debugger that can be used to debug SQL PL, users may not want to run a debugger in production. This session will explore alternatives to using the Unified Debugger. At the end of this session, you should be able to use the techniques discussed in this presentation to Debug an SQL PL application (Procedure, Function, or Trigger).

The mainframe, it’s just different…scalable, reliable, securable. But many in IT leadership roles think that “difference” is a barrier to success. It doesn’t have to be. The mainframe software has been evolving for years to be more and more manageable via user interfaces and commands that are similar or familiar to people using non-mainframe systems. The barrier to entry has been greatly reduced to enable simplified mainframe operation, monitoring, and performance management.  In this session, we show how IBM Db2 Tools can help to visualize Db2 for z/OS metrics, log information, real time statistics, and more in modern dashboards such as Grafana, IBM Instana or Elastic. This enables Db2 administrators and SMEs to detect anomalies, performance trends, and dependencies without need to navigate between multiple traditional user interfaces. Get to know new insights into your Db2 for z/OS systems with modern, state-of-the-art, and customizable user interfaces.

The AI-driven economy requires quicker responses to market changes, especially for high-demand mainframe Db2 applications, which are seeing increased usage to meet key business needs. To ensure smooth operations of critical workloads, businesses are turning to AI/ML to tackle Db2 performance issues. This enables System Db2 DBAs to predict bottlenecks and minimize business impact.

Discover how LinuxONE redefines the modern data platform. We explore how its architecture consolidates massive databases with minimal latency, extreme security, and high availability. Learn about vertical scalability, drastic software licensing savings, and how LinuxONE’s sustainability drives ROI, transforming your data center into an agile, resilient innovation engine designed for mission-critical workloads.

The main objective of the session is go to show all the available technical items and metrics that are being captured by relatively newer SMF 102 IFCID 365 records. The supplies a great deal of information and that can be drivers for monitoring, exceptions, alerts, trend analysis and much more. The IFCID 365 records are statistics records, and the session will show how you can join the data with Db2 accounting data to driver even more insight and knowledge. Also in the session it will be discussed how best to identify out of support drivers, where they are being initiated from and who the user of the driver is to be able to quickly know who to contact to address the out of support driver. Lastly, distributed workload transaction annotation will be discussed on the great value and the many ways the information can be exploited.

Production-ready AI applications don't happen by accident. They require well-architected, scalable, and maintainable data and AI pipelines. In this hands-on workshop, participants will build the two pipelines that most production AI applications depend on, using IBM Db2's modern AI stack, covering native vector storage, approximate vector indexing, and built-in integration with external AI models.

Participants will first build a Data Ingestion Pipeline that loads, processes, and transforms source content into searchable vectors, leveraging external AI models registered and called directly through Db2. They will then build a Search and Retrieval Pipeline that finds the most relevant data for any given query using Db2's native vector search capabilities, and delivers the most relevant results back to the application accurately and efficiently.

DBAs will recognize familiar ground here. The same principles that make a great database — performance, scalability, security, and maintainability — are exactly what separate a production AI application from a proof of concept. For AI engineers and application builders, this workshop offers something equally valuable: a solid, enterprise-grade data foundation that eliminates the complexity of managing separate vector stores and AI infrastructure, so they can focus on building intelligent applications faster.

Participants leave with hands-on coding experience building production-grade pipelines, along with the practical knowledge to tune for performance, scale for large workloads, and maintain AI applications with confidence over time.

Familiarity with SQL and basic database concepts is all that is needed.

Production-ready AI applications don't happen by accident. They require well-architected, scalable, and maintainable data and AI pipelines. In this hands-on workshop, participants will build the two pipelines that most production AI applications depend on, using IBM Db2's modern AI stack, covering native vector storage, approximate vector indexing, and built-in integration with external AI models.

Participants will first build a Data Ingestion Pipeline that loads, processes, and transforms source content into searchable vectors, leveraging external AI models registered and called directly through Db2. They will then build a Search and Retrieval Pipeline that finds the most relevant data for any given query using Db2's native vector search capabilities, and delivers the most relevant results back to the application accurately and efficiently.

DBAs will recognize familiar ground here. The same principles that make a great database — performance, scalability, security, and maintainability — are exactly what separate a production AI application from a proof of concept. For AI engineers and application builders, this workshop offers something equally valuable: a solid, enterprise-grade data foundation that eliminates the complexity of managing separate vector stores and AI infrastructure, so they can focus on building intelligent applications faster.

Participants leave with hands-on coding experience building production-grade pipelines, along with the practical knowledge to tune for performance, scale for large workloads, and maintain AI applications with confidence over time.

Familiarity with SQL and basic database concepts is all that is needed.

Production-ready AI applications don't happen by accident. They require well-architected, scalable, and maintainable data and AI pipelines. In this hands-on workshop, participants will build the two pipelines that most production AI applications depend on, using IBM Db2's modern AI stack, covering native vector storage, approximate vector indexing, and built-in integration with external AI models.

Participants will first build a Data Ingestion Pipeline that loads, processes, and transforms source content into searchable vectors, leveraging external AI models registered and called directly through Db2. They will then build a Search and Retrieval Pipeline that finds the most relevant data for any given query using Db2's native vector search capabilities, and delivers the most relevant results back to the application accurately and efficiently.

DBAs will recognize familiar ground here. The same principles that make a great database — performance, scalability, security, and maintainability — are exactly what separate a production AI application from a proof of concept. For AI engineers and application builders, this workshop offers something equally valuable: a solid, enterprise-grade data foundation that eliminates the complexity of managing separate vector stores and AI infrastructure, so they can focus on building intelligent applications faster.

Participants leave with hands-on coding experience building production-grade pipelines, along with the practical knowledge to tune for performance, scale for large workloads, and maintain AI applications with confidence over time.

Familiarity with SQL and basic database concepts is all that is needed.

Unlock the Power of Autonomous Database Management with Db2 Genius Hub. In this hands-on lab, we’ll explore how Db2 Genius Editions revolutionize database operations by embedding AI-native intelligence directly into the database control plane. Discover how the Db2 Genius Hub transforms database management, enabling DBAs to supervise AI-driven operations, and focus on optimization, governance, and driving digital innovation. Participants will gain insights into the benefits of intent-driven interaction, autonomous workflows, and the future of database management.

Unlock the Power of Autonomous Database Management with Db2 Genius Hub. In this hands-on lab, we’ll explore how Db2 Genius Editions revolutionize database operations by embedding AI-native intelligence directly into the database control plane. Discover how the Db2 Genius Hub transforms database management, enabling DBAs to supervise AI-driven operations, and focus on optimization, governance, and driving digital innovation. Participants will gain insights into the benefits of intent-driven interaction, autonomous workflows, and the future of database management.

Unlock the Power of Autonomous Database Management with Db2 Genius Hub. In this hands-on lab, we’ll explore how Db2 Genius Editions revolutionize database operations by embedding AI-native intelligence directly into the database control plane. Discover how the Db2 Genius Hub transforms database management, enabling DBAs to supervise AI-driven operations, and focus on optimization, governance, and driving digital innovation. Participants will gain insights into the benefits of intent-driven interaction, autonomous workflows, and the future of database management.