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Making the Move to IBM DB2 on Intel Xeon Processors Cutting costs and complexity while boosting performance for mission-critical workloads

Cutting costs and complexity while boosting performance for mission-critical workloads

Migrating to a new database platform or hardware architecture can seem daunting. Yet organizations might be driven to make a change to address key business goals. For example, a move from Oracle database to IBM DB2* can help reduce costs and complexity. Migrating databases from a Sun SPARC* infrastructure to IBM System x* servers based on Intel® Xeon® processors can increase database performance, consolidation, scalability, and availability.

Whatever the initial goals, moving to DB2 and IBM servers based on Intel Xeon processors can deliver significant benefits. Capabilities built into DB2 make the move from Oracle database as smooth and straightforward as possible.

Reducing costs and complexity with IBM DB2
IBM DB2 offers numerous features and capabilities that can help reduce costs compared with running Oracle database. For example, IBM DB2 Deep Compression* can help organizations significantly decrease storage costs by compressing tables, indexes, temp space, and XML data. With Deep Compression, organizations can reduce disk space up to 70 percent while simultaneously boosting performance. In addition, IBM offers highly accommodating virtualization licensing options that can help organizations reduce the costs of virtualization by moving to DB2.

By automating routine administrative tasks, IBM DB2 also can help reduce the complexity and costs of database management compared with managing an Oracle environment. Organizations can reduce staffing requirements and free up DBAs for higher-value projects.

IBM DB2 also offers more scalability options than Oracle database, accommodating a wider variety of distinct business and IT needs. For example, the IBM Database Partitioning Feature (DPF), available with the DB2-based IBM InfoSphere* Warehouse, enables organizations to incrementally scale data warehouse systems using a shared nothing approach to improve performance.

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