Flexible configurations

When you use Db2 data sharing, you can configure your system environment much more flexibly.

As the following figure shows, you can have more than one Db2 data sharing group on the same z/OS sysplex. You might, for example, want one group for testing and another for production data.

Figure 1. A possible configuration of Db2 data sharing groups. Although this example shows one Db2 for each z/OS system, your environment could have more.
Begin figure description. This Parallel Sysplex supports two data sharing groups and a single DB2 subsystem. End figure description.

You can also run multiple members on the same z/OS image (not shown in this figure).

Flexible operational systems

The following figure shows how, with data sharing, you can have query user groups and online transaction user groups on separate z/OS images. This configuration lets you tailor each system specifically for that user set, control storage contention, and provide predictable levels of service for that set of users. Previously, you might have needed to manage separate copies of data to meet the needs of different user groups.

Figure 2. Flexible configurations with Db2 data sharing. Data sharing lets each set of users access the same data, which means that you no longer need to manage multiple copies.
Begin figure description. In a data sharing environment, multiple user groups, each on its own z/OS image, can share the same data. End figure description.

Flexible decision support systems

The following figure shows two different decision support configurations. A typical configuration separates the operational data from the decision support data. Use this configuration when the operational system has environmental requirements that are different from those of the decision support system. The decision support system might be in a different geographical area, or security requirements might be different for the two systems.

Db2 offers another option—a combination configuration. A combination configuration combines your operational and decision support systems into a single data sharing group and offers these advantages:

  • You can occasionally join decision support data and operational data by using SQL.
  • You can reconfigure the system dynamically to handle fluctuating workloads. For example, you might choose to dedicate CPCs to decision support processing or operational processing at different times of the day or year.
  • You can reduce the cost of computing:
    • The infrastructure that is used for data management is already in place.
    • You can create a prototype of a decision support system in your existing system and then add processing capacity as the system grows.
Figure 3. Flexible configurations for decision support. Db2 data sharing lets you configure your systems in the way that works best within your environment.
Begin figure description. A typical configuration is shown side-by-side with a combination configuration. End figure description.

To set up a combination configuration, separate decision support data from operational data as much as possible. Buffer pools, disks, and control units that you use in your decision support system must be separate from those that you use in your operational system. This separation greatly minimizes any negative performance impact on the operational system.

If you are unable to maintain that level of separation or if you have separated your operational data for other reasons such as security, using a separate decision support system is your best option.

Flexibility to manage shared data

Data sharing can simplify the management of applications that must share some set of data, such as a common customer table. Maybe these applications were split in the past for capacity or availability reasons. But with the split architecture, the shared data must be kept in synch across the multiple systems (that is, by replicating data).

Data sharing gives you the flexibility to configure these applications into a single Db2 data sharing group and to maintain a single copy of the shared data that can be read and updated by multiple systems with good performance. This option is especially powerful when businesses undergo mergers or acquisitions or when data centers are consolidated.