DB2 12 for z/OS: Technical Overview and Highlights

by John Campbell and Gareth Jones

Introduction

Cloud, Analytics, and Mobile are changing the landscape for enterprise customers. These technology trends are partly driven by an explosion of data and partly by business needs to gain "deeper business insight" from data to improve business efficiency and effectiveness. The enterprise's data server is at the heart of this revolution, and it is important that the data servers are agile, secure, and provide seamless integration to these newer technologies. This paper will provide an overview of how DB2 12 addresses these business and technological needs.

Why You Should Read This Paper

This paper is targeted at IT Architects, such as Enterprise, System, Software, and Data Architects, who work with business leaders and subject matter experts. It will help architects ensure that business and IT are aligned and also ensure that they design and deliver an architecture that supports the most efficient and secure IT environment meeting an enterprise's business needs.

Highlights

This IBM® DB2® for z/OS® white paper provides a high-level overview of some of the key changes introduced in DB2 12 for z/OS, including the following topics:

• Performance for Traditional Workloads

• Performance Enablers for Modern Applications

• Application Enablement

• RAS — Reliability, Availability, Scalability, plus Security

• Migration and Prerequisites

Before looking at those areas in detail, it's important to put them in context in terms of the goals that the DB2 for z/OS development team set themselves, in four broad themes:

• Application enablement

• DBA function

• OLTP performance

• Query performance

Application Enablement

DB2 development set themselves the target of addressing a number of key customer requirements to expand the use of the existing features of DB2, as well as delivering mobile, hybrid cloud, and DevOps enablement. Two more objectives in the application enablement area were to provide enhance IDAA functionality to support an expanded number of use cases, and to provide incremental improvements in the SQL and SQL/PL areas to make DB2 ready for the next wave of applications.

DBA Function

Even with the existing capability to grow partitioned table spaces to 128 TB, some customers have been constrained by table and partition scalability limits, and addressing this issue has become one of the goals of this release. To complement this, another objective is to simplify large table management. Further goals are to remove the biggest inhibitors to 24 × 7 continuous availability and to provide incremental security and compliance improvements.

OLTP Performance

OLTP performance is still one of the biggest requirements for our customers, so the goal in this area is to build on the improvements in DB2 10 and DB2 11 to deliver even more performance improvements. For DB2 12, the goals are to reduce CPU consumption in the range of 5–10% by exploiting in-memory features, to double the throughput when inserting into a non-clustered table, to remove system scaling bottlenecks associated with high n-way systems, and to provide incremental improvements related to serviceability and availability.

Query Performance

Query performance for OLAP, BI, and other more complex workloads also remains a focus for our customers, and we have targeted four improvements in this area, to build on the work done in DB2 11: 20–30% CPU reduction for complex query workloads, improved efficiency delivered by reducing other resource consumption, a particular target of 80% for UNION ALL performance improvement; and simplified access path management, especially for dynamic SQL.

Quick Hits

Let's have a look at some of the highlights of this release before moving on to discuss the specific changes in detail.

Scale and Speed for the Next Era of Mobile Applications

DB2 development has measured over 1 million inserts per second, and we believe we can scale higher.

DB2 can also support up to 256 trillion rows in a single table, with agile partition technology.

In-memory Database

In-memory database is a major theme for this release. DB2 development has measured up to 23% CPU reduction for index lookup with advanced in-memory techniques.

Next-generation Application Support

In terms of next-generation application support, DB2 can now handle up to 360 million transactions per hour through a RESTful Web API into DB2.

Deliver Analytical Insights Faster

Response time is not just a requirement for OLTP workloads, but also for analytical workloads, where DB2 can deliver up to a two-times speed-up for query workloads, and for targeted queries, up to a 100-times speed-up.

Performance for Traditional Workloads

In this section, we'll look at changes in DB2 12 for z/OS that improve performance for traditional workloads.

In-memory Computing

DB2 12 places a strong emphasis on in-memory computing, combining large real memory size together with memory-optimized data structures to drive performance improvements. Unlike in prior releases, where some of the performance improvements were available without necessarily making use of more real memory available to DB2, many of the DB2 12 enhancements require customers to provision more real memory for DB2 to exploit before they can realise the significant performance gains. All the enhancements in this section require additional real memory. As a general comment on real memory provisioning, customers should plan to avoid all paging and make sure that they have sufficient free real memory to run safely.

In-memory Contiguous Buffer Pools

One of the features that falls into this category is the in-memory contiguous buffer pool. The objective of this buffer pool option is to cache entire table spaces or index spaces inthe buffer pool. The larger the object, the larger the buffer pool, and the larger the buffer pool, the more real memory is required.

The in-memory contiguous buffer pool improves performance and reduces CPU consumption by providing direct page access in memory — DB2 development has measured up to an 8% CPU reduction for OLTP workloads using...