Caches
Problem – Sometimes Persisting Data in a Cache is the Right Answer
Managing the performance of frequently-accessed data sources, in order to minimize impact on operational systems and to support service level agreements, can be a challenge in large scale data virtualization environments. When query optimization alone is not sufficient, caching provides an excellent alternative with greater agility and lower cost than traditional physical replication and consolidation techniques.
Solution – Use Caching to Flexibly Persist Data to Meet Service Level Needs
You can use Composite data virtualization in a number of ways to flexibly persist queried data in order to meet data delivery service level agreements and protect source system performance.
Any Composite service, view or procedure may be cached for future use, and all caches may be periodically and automatically refreshed to stay synchronized with their systems of record. Queries are processed against caches just as if you were querying the original data source.
In centralized mode, Composite can persist all cached data is stored in a single cache repository like Oracle, MySQL, Sybase or Teradata (there is no limit to the cache size). Composite’s centralized cache refresh is fully configurable including timed refresh, event-based refresh (CJM or JMS message), incremental refresh and forced refresh. For clustered deployment, this centralized cache reduces the need for each cluster node to re-fetch the data from the source, which significantly reduces the impact on production data sources.
In distributed mode, users dedicate one or mode Composite servers as edge servers and configure edge cache policies. Edge cache policies let you control which cache data is replicated from the central cache to the edge location and the refresh rules. Refresh can be time based, event-based or incremental. The edge cache should also be deployed in a relational database.
Composite also supports Oracle’s Coherence when it is configured as Hybernate’s L2 cache.
Caches
Selected Examples
- Caching Product Master Data to Optimize the Supply Chain – To optimize manufacturing efficiency and customer delivery, this leading PC provider uses Composite to combine product master data with customer demand data from their order entry systems, product inventory data from their distribution systems, and product work in process data from their manufacturing operations to provide supply chain planners with a global view of supply and demand. To improve query performance on the master data hub, Composite cached a subset of the product master data, the minimum required for identify supplies and demands. This allowed Composite to deliver to up-to-the-minute information required to fulfill orders more quickly, accelerate revenue, and increase inventory turns.
