Database Reference
In-Depth Information
High service performance combined with
High Availability
Extracting the highest possible performance in events processing or in any distributed com-
puting systems for that matter can be achieved only if we can leverage data caching. A new
layer called data grid as a distributed in-memory processing fabric must be established
around most I/O and processor-consuming frameworks and service resources, primarily
around ESB and databases. Regarding service resources and DB in particular, the cluster-
ing technique has been around for quite a long time; therefore, we doubt that your mission-
critical DBs are not installed on RAC using SAN and so we will not dwell into it.
To serve HA and high-performance purposes, this fabric must satisfy certain criteria:
• Data Grid/fabric partitioning around a resource-consuming framework must be dy-
namic and automatic; that is, you should be able to add new servers into the
cluster, automatically change the partition, and consequently, data replication and
the processing workload.
• The amount of data distributed around every grid node must be configurable.
• The aggregate data throughput of the fabric is linearly proportional to the number
of servers.
• The in-memory data capacity and data-indexing capacity of the fabric is linearly
proportional to the number of servers.
• The aggregate I/O throughput for disk-based overflow and disk-based storage of
data is linearly proportional to the number of servers.
• Partitioning must provide load balancing and a configurable level of data redund-
ancy to maintain the required level of data resiliency (usually, zero tolerance to
data losses).
• As every node should maintain data management (I/O processing) at the propor-
tional level, the scalability rate must be close to the linear and directly proportional
to the number of nodes in a data grid cluster.
• As a logical outcome from the preceding points, the more nodes in the grid, the
more resilient the fabric would be.
• Another logical outcome is that the number of served clients (task submitters) is
proportional to the number of nodes in the grid. Proportion must be linear, of
course.
• Clients (task submitters) must see this fabric through a unified interface, com-
pletely decoupling the client from the fabric's size/complexity.
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