Topology Types
Standalone – The data set is held in the application node. Any other application nodes are independent with no communication between them. If a standalone topology is used where there are multiple application nodes running the same application, then there is Weak Consistency between them. They contain consistent values for immutable data or after the time-to-live on an element has completed and the element needs to be reloaded.
Distributed – The data is held in a remote server (or array of servers) with a subset of recently used data held in each application node. This topology offers a rich set of consistency options.
A distributed topology is the recommended approach in a clustered or scaled-out application environment. It provides the highest level of performance, availability, and scalability. The distributed topology is available only with BigMemory Max.
Replicated – The cached data set is held in each application node and data is copied or invalidated across the nodes without locking. Replication can be either asynchronous or synchronous, where the writing thread blocks while propagation occurs. The only consistency mode supported in this topology is Weak Consistency.
Many production applications are deployed in clusters of multiple instances for availability and scalability. However, without a distributed or replicated cache, application clusters exhibit a number of undesirable behaviors, such as:
Cache Drift - If each application instance maintains its own cache, updates made to one cache will not appear in the other instances. This also happens to web session data. A distributed or replicated cache ensures that all of the cache instances are kept in sync with each other.
Database Bottlenecks - In a single-instance application, a cache effectively shields a database from the overhead of redundant queries. However, in a distributed application environment, each instance must load and keep its own cache fresh. The overhead of loading and refreshing multiple caches leads to database bottlenecks as more application instances are added. A distributed or replicated cache eliminates the per-instance overhead of loading and refreshing multiple caches from a database.