Db2 for z/OS is one the most business-critical products in the IBM portfolio and remains core to many transaction processing, advanced analytics, and machine learning initiatives.
Over the past 35 years Db2 has been on an exciting and transformational journey. Retired IBM Fellow Edgar F. Codd published his famous paper in 1969 “A Relational Model of Data for Large Shared Data Banks“. From that, “Sequel” – later renamed SQL – was born.
Db2 launched in 1983 on MVS but Don Haderle (retired IBM Fellow and considered to be the “father of Db2”) views 1988 as a seminal point in its development as DB2 version 2 proved it was viable for online transactional processing (OLTP), the lifeblood of business computing at the time.
Thus was born a single database and the relational model for transactions and business intelligence.
Success on the mainframe led to the port to open systems platforms, like UNIX, Linux and other platforms on both IBM and non-IBM hardware.
Db2 helped position IBM as an overall solution provider of hardware, software and services. Its early success, coupled with IBM WebSphere in the 1990s put it in the spotlight as the database system for several Olympic games — 1992 Barcelona, 1996 Atlanta and the 1998 Winter Olympics in Nagano. Performance was critical – any failure or delays would be visible to viewers and the world’s press as they waited for event scores to appear.
Mainframes continue to store some of the world’s most valued data. The platform is capable of 110,000 million instructions per second, which (doing the math) translates into a theoretical 9.5 trillion instructions per day. With such high-value data, some of which holds highly sensitive financial and personal information, the mainframe becomes a potential target for cyber-criminals. Thankfully, the IBM Z platform is designed to be one the most securable platforms. Another key capability of the platform is the integrity of the z/OS system and IBM’s commitment to resolve any integrity-related issues.
Db2 for z/OS is a strong foundation for the IBM Z analytics portfolio with the latest iteration, version 12, providing enhanced performance over the previous version. Db2 leverages the reliability, availability and serviceability capabilities of the IBM Z platform, which delivers five nines (99.999) percent—near continuous data availability.
Advanced in-memory techniques result in fast transaction execution with less CPU, making Db2 an in-memory database. Rich in security, resiliency, simplified management and analytics functionality, Db2 continues to provide a strong foundation to help deliver insight to the right users, at the right time.
The ability to ingest hundreds of thousands of rows each second is critical for more and more applications, particularly for mobile computing and the Internet of Things (IoT) where tracking website clicks, capturing call data records for a mobile network carrier, tracking events generated by “smart meters” and embedded devices can all generate huge volumes of transactions.
Many consider a NoSQL database essential for high data ingestion rates. Db2 12, however, allows for very high insert rates without having to partition or shard the database — all while being able to query the data using standard SQL with Atomicity, Consistency, Isolation, Durability (ACID) compliance.
In 2016 Db2 for z/OS moved to a continuous delivery model that delivers new capabilities and enhancements through the service stream in just weeks and sometime days instead of multi-year release cycles. This helps deliver greater agility while maintaining the quality, reliability, stability, security requirements demanded by its customer base.
We also enhance performance with every release and now provide millions of inserts per second, trillions of rows in a single table, staggering CPU reductions…. the list goes on.
Db2 for z/OS is the data server at the heart of many of today’s data warehouses, powering IBM analytics solutions such as Cognos, SPSS, QMF, ML for z/OS, IBM DB2 Analytics Accelerator and more. In short, Db2 creates a sense of “Data Gravity” where its high value prompts organizations to co-locate their analytics solutions with their data. This helps remove unnecessary network and infrastructure latencies as well as helping reduce security vulnerabilities. The sheer volume and velocity of the transactions, the richness of data in each transaction, coupled with data in log files, is a potential gold mine for machine learning and A.I. applications to exploit cognitive capabilities and do smarter work, more intelligently and more securely. And so Machine Learning for z/OS was released, built on open source technology, leveraging the latest innovations while making any perceived complexities of the platform transparent to data scientists through the IBM Data Science Experience interface.
The future is hybrid cloud. Customers will always need on-prem data and applications but the move to cloud (public or private) is in high demand. We see the opportunity to help customers reduce capital and management costs, enabling them to focus on running their data and advanced analytics to create business advantages while providing a dynamic, elastic scale-out infrastructure in the cloud from any of our data centers around the world. Cloud-enabling applications and middleware such as Db2 for z/OS also helps clients to rapidly provision new services and instances on demand — again for both public or private cloud.
To the end user, the processing platform is (and should be) transparent to them and transparent to the applications that connect to or through DB2 for z/OS.
We recognize the draw of cloud — and how fast it’s changing. It’s why this DBMS offering continues to leverage a continuous delivery model to speed this transformational journey.
Our “One Team” approach has made this work possible. Many talented people participate in this work but some of the key players driving the effort are Namik Hrle – IBM Fellow, and Distinguished Engineers Jeff Josten and John Campbell.
Your next move…
Dinesh Nirmal – Vice President, IBM Analytics Development
Follow me on Twitter: @dineshknirmal