Some Under-the-Radar Db2 13 for z/OS Features to Consider

Db2 13 for z/OS has been available for some time now, and soon (December 2025) it will be the only version of Db2 supported by IBM. So, we all should be either using Db2 13 already, or well into the process of migrating to Db2 13.

With that in mind, here are a few a lesser-known but compelling new features in Db2 13 for z/OS. That is, these enhancements have not received as much attention as the more news-hogging AI and performance new features. 

Online Removal of Active Log Datasets 

It is now possible to remove active log data sets while Db2 is up and running. This new capability is available in Function Level 500 and above. This can be accomplished using 

–SET LOG REMOVELOG 

Using this new option of the -SET LOG allows you to safely remove an active log data set from the BSDS without requiring downtime—as long as the data set isn't currently in use.

• If the data set is in use, the data set will be placed in a “REMOVAL PENDING” state, making it unavailable moving forward, until explicitly handled.

• If it's the next log to be written, the command fails with “REMOVAL PROHIBITED.”

• You can monitor this using -DISPLAY LOG DETAIL and use D GRS,RES=(*,dsname,*) to check log usage.

This feature greatly reduces operational risk and complexity during log maintenance in active environments.

DDL Lock Management

Db2 13 adds several new controls that help improve availability and reduce contention when performing DDL (data definition) operations:

• CURRENT LOCK TIMEOUT special register: Lets you override the system-level lock timeout (IRLMRWT) on a per-statement basis (values from 1–32767 seconds), limiting how long transactions queue behind DDL.

• DEADLOCK_RESOLUTION_PRIORITY global variable: Assigns a numerical priority (0–255) to help determine which process is likely to win in a deadlock. Higher values make a DDL process less likely to be chosen as a deadlock victim.

• System monitor profiles can now be configured — for both local and remote applications — to automatically set these values and even adjust package release behavior between RELEASE(COMMIT) and RELEASE(DEALLOCATE).

These features provide more granular control over lock management and thereby should help us reduce disruptions, improve the responsiveness of DDL, and help maintain service levels across transactional workloads.

Why These Features Deserve More Spotlight

• Operational impact without fanfare: While AI functions and accelerator improvements grab headlines, these enhancements quietly deliver high-impact capabilities—especially in high-availability, non-stop environments.

• Prevents outages during routine tasks: The ability to remove log datasets live and better manage DDL locking improves reliability and uptime for critical systems.

• Real-world value for DBAs and sysprogs: These are features that seasoned Db2 for z/OS professionals will deeply appreciate—and can use to simplify otherwise risky operations.

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Bonus: Other Less-Heralded, but Useful Enhancements

From the 2024 continuous delivery updates (without function-level control), these two new capabilities also seem to be flying under the radar:

• Database utilities running on zIIP: APAR PH63832 allows portions of the COPY utility to leverage zIIP processing, reducing CPU costs.

• Targeted statistics deletion: APAR PH63145 lets you delete catalog statistics for a specific partition—without touching the whole object.

Maybe I have missed your favorite under the rader Db2 13 enhancement? If so, please share it with the community in a comment below!

Mainframe Relevance in an AI-First Era: How Db2 Fits

For decades, the IBM Z mainframe has been the backbone of mission-critical computing. Db2 for z/OS sits at the center of this story, reliably managing the world’s most sensitive and high-value data. Yet in today’s IT landscape, dominated by discussions of artificial intelligence (AI), machine learning, and data-driven transformation, the question inevitably arises: 

Where does Db2 fit in an AI-first world?

The answer is clear: Db2 remains central. In fact, it is uniquely positioned to power and support enterprise AI initiatives.

The Foundation of Trustworthy Data

AI is only as good as the data that feeds it. Models trained on incomplete, inconsistent, or inaccurate data produce unreliable outcomes. This is where Db2 shines. With its proven capabilities for data integrity, security, and availability, Db2 for z/OS provides the foundation of trustworthy, enterprise-grade data that AI depends upon.

Organizations already store their most critical operational data in Db2. Leveraging this data directly—without needing complex ETL processes that move it into less secure environments—offers a significant advantage. AI workloads can run against reliable, current data with governance and compliance controls already in place.

Db2 and Embedded AI Capabilities

IBM has not stood still in bringing AI to Db2 for z/OS. For example, Db2 AI for z/OS (Db2ZAI) uses machine learning models to improve database performance. By analyzing workload patterns, Db2ZAI can recommend optimal buffer pool configurations, predict query performance, and even assist the optimizer in choosing the best access paths. This closes the loop: AI is being applied inside Db2 itself to make database management more intelligent and efficient.

Similarly, SQL Data Insights brings AI-powered analytics directly into Db2 for z/OS, enabling built--in SQL functions to use AI for anomaly detection and data pattern recognition without requiring external AI platforms. These capabilities allow organizations to unlock the hidden value in their Db2 data more quickly and intuitively.

Synergy with IBM Z and AI Acceleration

The hardware platform itself reinforces this story. The latest IBM z16 and z17 mainframes incorporate on-chip AI acceleration with the Telum processor and Spyre AI accelerator. This means that inferencing can be performed where the data resides, avoiding latency and risk associated with data movement. For financial institutions detecting fraud, retailers optimizing transactions, or insurers assessing claims, the ability to apply AI in real-time on operational data is transformative.

Db2, running on these systems, is directly positioned to take advantage of this capability—turning the mainframe into not just a system of record, but also a system of insight and decision.

The DBA’s Evolving Role in an AI-First Era

As AI integrates more deeply into Db2, the role of the DBA also evolves. No longer solely the guardian of performance tuning and availability, the modern DBA must understand how AI tools are being embedded in their environment. This includes evaluating AI-driven recommendations, integrating AI queries into business applications, and ensuring that AI workloads are governed and secure.

Rather than diminishing the DBA’s importance, AI amplifies it. Human expertise is needed to validate, interpret, and operationalize AI-driven insights in ways that align with business priorities and regulatory requirements.

Conclusion

The narrative that positions mainframes and Db2 as “legacy” is misguided. In reality, Db2 for z/OS sits at the heart of enterprise AI adoption. With its unmatched reliability, native AI capabilities, and synergy with IBM Z’s AI-accelerated hardware, Db2 is not only relevant but critical in an AI-first world.

For organizations pursuing AI, the best path forward often starts with the data they already trust most—residing in Db2. The mainframe is not being left behind by AI; it is, in fact, helping to lead the way.

Machine Learning and AI Integration in Db2 for z/OS

In today’s data-driven world, the ability to harness the power of machine learning (ML) and artificial intelligence (AI) is essential for organizations aiming to stay competitive. With the introduction of Db2 for z/OS Version 13 and subsequent function levels, IBM has made significant strides in integrating ML and AI capabilities directly into the Db2 ecosystem, transforming the way businesses leverage their data.

SQL Data Insights

Perhaps the single most important new AI capability added to Db2 13 for z/OS is SQL Data Insights (SDI). I have written about this before and if you are interested in a more thorough discussion of SDI, check out this article on elnion.

At a high level though, SDI enables data scientists and analysts to run advanced analytics directly on data residing in Db2 without the need for extensive data movement. By minimizing data transfer, organizations can reduce latency and improve the efficiency of their workflows.

The initial support for SDI in Db2 13 for z/OS FL600 included three AI functions: AI_SIMILARITY, AI_SEMANTIC_CLUSTER and AI_ANALOGY. Function level 504 added a fourth: AI_COMMONALITY.

Python Support

Python is the dominant programming language for AI and ML because of its simplicity, readability, and vast ecosystem of libraries. It offers clear syntax allowing data scientists and developers to focus on solving problems rather than wrestling with complex code structures. This makes it ideal for rapid prototyping of AI models. Rich frameworks such as TensorFlow, PyTorch, and others provide ready-to-use tools for data preparation, model training, and evaluation, significantly reducing development time. Moreover, Python’s large, active community continually contributes new algorithms, techniques, and integrations, ensuring that it stays at the forefront of AI and ML innovation. This combination of usability, flexibility, and ecosystem maturity has made Python the de facto standard for building, deploying, and operationalizing AI and ML solutions across industries.

With Python being so important to data scientists, it stands to reason that IBM should support it in Db2 for z/OS. And they do! Python support for Db2 for z/OS was delivered with the IBM Db2 AI for z/OS and the Db2 for z/OS Python driver as part of the IBM Db2 for z/OS “Data Server Driver for ODBC, CLI, and .NET” family.

• IBM Db2 AI for z/OS (Db2ZAI) is an advanced solution designed to enhance the operational performance, reliability, and efficiency of Db2 for z/OS systems. By leveraging machine learning (ML) and artificial intelligence (AI), it improves many aspects of Db2 management. We will discuss it in a little more detail in the next section.
• The Python driver is IBM's official database connectivity driver that allows Python applications to connect to and interact with IBM DB2 databases. It delivers connectivity not just for Db2 for z/OS, but also for other IBM database products including DB2 for Linux/Unix/Windows, DB2 for i (AS/400), and IBM Informix.

So, Python support became generally available via IBM Db2 for z/OS Distributed Data Facility (DDF) using the IBM Data Server Driver for Python, which is the same Python driver used for Db2 LUW, but configured to connect over DRDA to Db2 for z/OS.

This wasn’t tied to a specific Db2 function level—rather, it was an enhancement to the client connectivity stack and supported back to Db2 11 for z/OS with the right PTFs. Of course, as of this December (2025) Version 13 will be the only supported version of Db2 for z/OS.

Machine Learning Enhanced Optimization

The Db2 optimizer can also benefit from an infusion of AI. Optimization improvement is a benefit of IBM’s Db2 AI for z/OS, an add-on solution that uses AI/ML to elevate system operations and performance.

IBM Db2 AI for z/OS continuously analyzes workload patterns, system metrics, and SQL execution behavior to recommend or automatically apply optimizations—such as selecting better access paths, tuning buffer pools, or adjusting configuration settings to reduce CPU usage. By learning from an organization’s actual Db2 workload over time, it adapts its recommendations to evolving data and usage patterns, helping maintain consistent performance without constant manual tuning.

In addition, Db2 AI for z/OS can assist in workload management, anomaly detection, and operational decision-making, giving DBAs intelligent, data-driven insights to run large-scale mainframe database systems more efficiently. By incorporating machine learning into key processes it can help to reduce CPU usage, optimize SQL query plans and concurrency, and detect and resolve anomalies and root causes.

Indeed, the AI-driven operational support of Db2 AI for z/OS goes beyond using AI in SQL queries. It is focused on keeping Db2 for z/OS environments running optimally and proactively, enhancing system resiliency and availability.

Summing Things Up

IBM continues to integrate machine learning and AI capabilities into Db2 for z/OS. By empowering organizations to leverage their data for predictive analytics and advanced machine learning, IBM is helping businesses unlock new opportunities and drive smarter decision-making. As these technologies continue to advance, the potential for innovation and growth in the data landscape is limitless. Embrace the future of data with Db2 for z/OS and unleash the power of AI and machine learning in your organization today!

Consider DBHawk as a Data Studio Replacement

Although IBM Data Studio is still available, its support and feature focus for Db2 have shifted significantly. Things are a little different for z/OS and LUW environments though. So, let’s take a look at the current situation with IBM Data Studio and then look at Datasparc’s DBHawk as a possible replacement.

The Data Studio Situation

For Db2 for z/OS, IBM is phasing out Data Studio for mainframe use. Perhaps “phasing” is too soft of a term – “has already phased” is more appropriate. Data Studio support for Db2 z/OS ended March 31, 2025. This means that IBM is no longer providing standard support for Data Studio for Db2 for z/OS. Furthermore, Data Studio does not officially support Db2 for z/OS Version 13 and later. Db2 13 is the current version of Db2 for z/OS and support for DB2 12 for z/OS itself ends on December 31, 2025. So, time is running out if you still rely on Data Studio for mainframe Db2.

IBM touts two different potential replacements for Data Studio from within its product portfolio:

• Db2 Administration Foundation – a browser‑based tool for Db2 z/OS DBAs.
• Db2 Developer Extension – a free Visual Studio Code extension tailored for SQL application development.

Replacing one tool with two has caused some confusion and dissatisfaction within the Db2 for z/OS community. Regarding Db2 Administration Foundation, it is not easy to install. Data Studio users are accustomed to just downloading the software to their PC and using it. Installing Admin Foundation requires additional systems software (Zowe and IBM Unified Management Server) necessitating the involvement of systems programmers. As such, many sites have delayed moving forward with Admin Foundation.

The Db2 Developer Extension is easier, but it requires you to use Microsoft Visual Studio Code. Not every organization does so.

For Db2 LUW (Linux, UNIX, Windows), IBM Data Studio continues to work. The product page confirms it remains the integrated environment for database development and administration across LUW IBM. However, the latest stable release is Data Studio 4.1.x, with version 4.1.4 released in late 2021. Four years is an eternity between software releases and given the current state of Db2 for z/OS support for Data Studio it may be wise even for Db2 LUW users to look for longer-term alternatives.

DBHawk: An Interesting Alternative

Datasparc DBHawk is a comprehensive, web-based platform designed for secure database management, application development, and data analytics across a wide range of databases, including IBM Db2 (both LUW and z/OS). Its unified IDE and security-centric features make it especially valuable for organizations seeking to streamline workflows, enhance collaboration, and maintain robust data governance.

DBHawk can be used to develop and manage Db2 databases and applications in several impactful ways:

• Web-Based SQL Development: DBHawk offers an advanced SQL editor with a user-friendly web interface that supports building, modifying, and executing SQL queries for Db2, eliminating the need for desktop installation and enabling access from anywhere.
  
  
• Cross-Database Compatibility: While IBM Data Studio focuses primarily on Db2, DBHawk supports multiple databases including Db2, Oracle, SQL Server, PostgreSQL, MySQL, AWS RDS, and many more. This makes it ideal if your environment includes heterogeneous databases or if you plan to expand beyond Db2.
  
  
• Text-to-SQL (AI Integration): The new text-to-SQL feature allows users to interact with Db2 using natural language, lowering the barrier for non-SQL experts to query data. This is an optional feature and administrators can control this feature to turn on or off.
  
  
• Centralized Security and Auditing: DBHawk provides robust centralized security features, including data access policies and auditing capabilities, helping organizations meet compliance requirements such as GDPR and HIPAA. 
  
  
• Self-Service Reporting and Dashboards: Beyond database development, DBHawk includes business intelligence tools like dynamic SQL charts and dashboards, enabling developers and analysts to create reports directly within the platform. IBM Data Studio lacks integrated BI/reporting features.
  
  
• Collaboration and Sharing: Teams can share SQL queries, reports, dashboards, and code snippets securely, supporting collaborative development and analytics.
  
  
• Automation and Batch Job Management: DBHawk supports automating SQL tasks and batch jobs through its web platform, streamlining routine database administration and development workflows, which can improve productivity compared to IBM Data Studio’s manual processes.
  
  
• No Client Installation: Being a browser-based tool, DBHawk requires no client installation, simplifying deployment and updates across teams.

DBHawk supports flexible deployment options, including Docker, Kubernetes, and cloud services, and integrates with enterprise authentication systems (SAML, LDAP, SSO). It is suitable for both on-premises Db2 installations and cloud-hosted instances (e.g., Amazon RDS for Db2).

Of course, DBHawk does not 100% replace all the functionality of Data Studio. If you rely on Data Studio for IDAA administration or require visual Explain functionality, DBHawk probably will not be helpful for those tasks.

Nevertheless, DBHawk can serve as a versatile, centralized, and web-accessible alternative to IBM Data Studio for Db2 development and management, especially if your needs extend to multi-database environments, enhanced security compliance, and integrated reporting capabilities.

Summary

DBHawk provides a modern, secure, and highly collaborative environment for Db2 application development and database management, combining advanced development tools, automation, and enterprise-grade security in a single web-based platform. This makes it an effective solution for organizations seeking to improve productivity, enhance data security, and simplify compliance in their Db2 environments.

IDUG Db2 Tech Conference 2025 Highlights

I had the good fortune to attend the North American IDUG Db2 Tech Conference in Atlanta, Georgia the week of June 8 through June 12, 2025, and as usual, the conference was phenomenal. If you are a Db2 developer, DBA, consultant, or user of any type there was a ton of content being shared. And there were many opportunities to mingle with peers to discuss and share your Db2 tips, tricks, and experiences. And that is probably the most beneficial part of the whole IDUG experience.

I’ve been going to IDUG conferences for a long time now. I’ve been to them all except the very first one. And yes, IDUG has changed a lot over the years, but it is still the preeminent user experience for Db2 professionals… that is, it is not to be missed!

So there I was on Monday morning, one of the many attendees filing into the opening session expectantly...

I took a seat among the crowd... and the first key takeaway from the event for me is that there are more new attendees going to IDUG than ever before. It was stated at the opening session that about 10 percent of attendees were first-timers. That is great news because the more new people exposed to IDUG the better! Even better, it was announced that there are over 16,000 IDUG members now.

The first keynote session, on Monday, was sponsored by IBM and it was titled Leveraging your Db2 Data for Enterprise AI. The keynote featured Minaz Merali, Vice President, IBM Z Data & AI and Priya Srinivasan, Vice President, IBM Core Software Products, Software Support & SRE. And yes, this session was heavy into IBM’s AI strategy, which is appropriate as AI is the driving force of IT these days. Indeed, it was said that IBM is branding itself as the hybrid cloud and AI company!

Another interesting tidbit from the keynote is that "Today only 1% of enterprise data is currently being leveraged by GenAI." So, we've still go a long way to go! Also, 90% of enterprise data is unstructured, which requires a completely different way of processing and analyzing than traditional, structured data. 

The speakers also identified four primary ways to scale AI with Db2 across the enterprise: application building, human productivity, performance, and integration. 

And it sure felt good to hear IBMers promoting Db2 loudly for all to hear. It sometimes feels like Db2 is a forgotten jewel that IBM doesn't promote as much as they should. But it does not feel that way at IDUG. The keynote speakers hammered home the point that IBM Db2 powers the modern economy! 

The top ten largest banks, insurance, and auto companies all rely on Db2! And 70 percent of the world's transactions run on the IBM Z mainframe.

But perhaps my favorite comment of the IBM keynote session was made by a user, Chris Muncan (Sr. Mainframe Db2 DBA at Sun Life), who was participating as part of a user panel. He called “legacy” systems “legendary” instead! I think I'm going to use that.

As an aside, I started feeling old as I listened to people talking about 15 or 20 years of experience and realizing that is still post-2000! I sometimes still think of 20 years ago as being in the 1980s!

I also delivered two presentations myself at IDUG. The first one was Monday, right after lunch, titled "Index Modernization in Db2 for z/OS." The general thrust of the presentation is that technology is evolving, and Db2 has changed a lot. As such, the same indexing strategies that worked well 10 or 20 or more years ago are no longer optimal. The presentation started with a brief review of the critical role of indexes and their history in Db2 for z/OS. Then I covered the many innovations IBM has applied to indexes in Db2 for z/OS over the past few releases including things like index compression, Fast Traverse Blocks (FTBs), and index features like include columns and indexing on expressions. Here I am talking about one of the newer index features, FTBs:

I also reviewed some of the many other changes that could impact indexing strategy including changing data patterns, analytics and IDAA, data growth, and the surge in dynamic SQL. Then I took at look at ways to examine your current index deployment and looking for ways to modernize and improve indexing at your shop.

Well, the topic must have struck a chord with attendees because I was ranked as the best user speaker at the conference! 

Thank you to all of the attendees who ranked my topic so highly, I am truly appreciative!

Later in the day the vendor expo hall opened and all the attendees were able to talk to the vendors about their products. I always take advantage of this great opportunity to chat up the knowledgeable folks at the vendor booths. Indeed, last year I was able to talk to the Rocket Software team to add a crucial feature to the Db2 Admin Tool for a client of mine!

This year, I also spent some time with the InfoTel team at their booth to help them promote their DB/IQ solutions for Db2 for z/OS. 

And two lucky winners walked away with a copy of my book, A Guide to Db2 Performance for Application Developers.

Day two opened with a keynote session from Greg Lotko of Broadcom - a fun session tying local "treasures" of Atlanta to Broadcom's Db2 solutions. 

Tuesday was also the day I delivered my second presentation, an updated version of My Db2 Top Ten Lists, which I first presented over 20 years ago at IDUG. Of course, this version was almost entirely new, but also contained some gems from past iterations of the lists. The lists run the spectrum of Db2 topic areas and provides me the opportunity to discuss a wide array of different Db2-related “things.” 

Of course, there were many more great sessions at IDUG from the likes of Tony Andrews, Thomas Bauman, Roy Boxwell, Brian Laube, Chris Muncan, and many more. I cannot list every great speaker from the event or this post would run on forever, and it is already quite long. But the complete grid of presentations and speakeds can be viewed on the IDUG website here. A few other things that I want to mention are:

• The great Women in Technology keynote session from day three "Harnessing the Power of Adaptability, Innovation, and Resilience" delivered by Jennifer Pharr Davis. 
• The Db2 for z/OS Spotlight session where Haakon Roberts illuminated everybody on highlights of how to prepare for the future of Db2 for z/OS.
• And the Db2 for z/OS Experts Panel - which is always a highlight of the event for me - where a body of IBM and industry luminaries take questions about Db2 for z/OS from the attendees.

Finally, there were nightly events hosted by the vendoes but the only one I attended this year was the IBM outing held at the Georgia Aquarium. The aquarium is one of the largest in the world and it contains some very large aquatic beasties including whale sharks, beluga whales, manta rays, and more. Here are some photos:

All in all it was a great week... if you are an IT professional who works with Db2 in any fashion, be sure to plan your trip to the next IDUG event in your area!