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Caching technology comparison


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This is a series of posts comparing Dynacache with other caching technologies:

This is a series of posts comparing Dynacache with other caching technologies:

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    • 1. Dynacache vs Memcached - Caching Technologies for Java Applications
    • 2. Technologies
      • General object cache attributes
      • Memcached
      • DistributedMap (part of Dynacache)
    • 3. General Object Cache Characteristics
      • An object cache is a Key-Value lookup table
        • Similar to a java.util.Hashtable
      • Have configurable maximum sizes
        • May be configured number of cache entries or memory size
        • Objects typically discarded on least-recently-used policy when cache is full
          • Some caches may offer other algorithms
      • Have configurable lifetimes per cache entry
    • 4. Overview: Memcached
      • “ Free & open source, high-performance, distributed memory object caching system” (from
      • Main components:
        • memcached server – standalone server storing cached items
        • memcached client software
          • Available for multiple programming languages
          • Keys & values must be transmitted over TCP/IP
      • Cluster design:
        • Client uses hashing algorithm to assign keys to servers
        • Each key is cached on at most one server
        • Explicit invalidations go only to the server which should store that key
    • 5. Overview: DistributedMap
      • Built-in component in WAS Network Deployment
        • Only available to Java clients
      • Content is cached in JVM memory
        • Cache operations are POJO calls
      • Multiple cache instances can be created
        • Each is treated separately for synchronization, LRU and invalidation
      • Cluster design:
        • Cache keys may be cached in multiple nodes
        • Explicit invalidation notifies peers to discard the cache key
        • Option available to push entries to peers on cache insert
    • 6. Advantages of Each Technology
      • Dynacache
        • Memory and disk storage for cache with ability to restrict size in terms of # of entries and # of bytes
        • Fast cache operations
          • The key raison d'etre for a cache
          • Lookups through POJO calls - no network delays
          • No serialization/ deserialization of keys and values – lower CPU consumption
        • Mature, well-supported part of WAS
          • Used in Connections, other ICS products
          • “ We know the developers”
        • Priority-based cache algorithm available
        • Variety of tools available for Administering, Monitoring and Configuration integrated with WAS
          • Mbean, Extended Cache Monitor
        • Higher QOS with WebSphere eXtreme scale integration
        • Leverages scalable, resilient and field tested WAS replication & HAManager infrastructure
        • Comprehensive cache metrics available including mbean and PMI statistics
        • Can be plugged in as an OpenJPA L2 cache
      • Memcached
        • Does not consume memory in Java heap
          • This is less important as we move to 64-bit JVMs
        • Single instance of each cache key
          • No peer-to-peer traffic on invalidations
        • Usable in Tomcat, WAS CE, php applications