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Shared-Disk Clustering

A shared-disk clustering approach increases the reliability of IT systems by providing multiple redundancies in the case of failure. It also maximizes the utilization of hardware resources and provides the foundation for future growth.

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Protect service levels and improve hardware utilization

Sybase Adaptive Server Enterprise (ASE) Cluster Edition allows mission-critical databases to run on multiple hardware servers using a shared-disk clustering architecture. By running on multiple servers, a shared-disk cluster architecture ensures the database service continues to run even if one or more of the nodes in the cluster is unavailable.

By combining virtualization and clustering techniques, organizations can reduce the complexities of managing and maintaining multiple workloads on a single cluster. This is the key to maximizing server resources.

With Sybase technology, you can:

  • Ensure 24x7 uptime with rapid failover when one or more machines fail simultaneously;
  • Replace underutilized standby servers with a cluster of machines i.e. clustered nodes can simultaneously support an active workload while providing standby service to other applications;
  • Manage efficient migration of departmental servers into centralized data centers;
  • Provide mission-critical service levels to departmental systems — while reducing administrative overhead and costs;
  • Harness more value from investments in new higher-capacity hardware by consolidating multiple databases onto a cluster of new machines;
  • Provide dynamic resource distribution based on user demands through Virtualized Resource Management™; and
  • Provide a reliable, efficient platform for grid and cloud computing.

Sybase is the only database vendor to combine shared-disk clustering and virtualization into one product. This allows enterprises to protect database service availability against server failures as efficiently and effectively as possible. Our unique Virtualized Resource Management (VRM) technology supports workload allocation across multiple cluster nodes, increasing the manageability of the database servers and allowing IT to maximize the use of each hardware resources of each individual server.