Chapter 2. Data Grid Caches
Data Grid caches provide flexible, in-memory data stores that you can configure to suit use cases such as:
- boosting application performance with high-speed local caches.
- optimizing databases by decreasing the volume of write operations.
- providing resiliency and durability for consistent data across clusters.
2.1. Cache Interface
Cache<K,V> is the central interface for Data Grid and extends java.util.concurrent.ConcurrentMap.
Cache entries are highly concurrent data structures in key:value format that support a wide and configurable range of data types, from simple strings to much more complex objects.
2.2. Cache Managers
Data Grid provides a CacheManager interface that lets you create, modify, and manage local or clustered caches. Cache Managers are the starting point for using Data Grid caches.
There are two CacheManager implementations:
EmbeddedCacheManager- Entry point for caches when running Data Grid inside the same Java Virtual Machine (JVM) as the client application, which is also known as Library Mode.
RemoteCacheManager-
Entry point for caches when running Data Grid as a remote server in its own JVM. When it starts running,
RemoteCacheManagerestablishes a persistent TCP connection to a Hot Rod endpoint on a Data Grid server.
Both embedded and remote CacheManager implementations share some methods and properties. However, semantic differences do exist between EmbeddedCacheManager and RemoteCacheManager.
2.3. Cache Containers
Cache containers declare one or more local or clustered caches that a Cache Manager controls.
Cache container declaration
<cache-container name="clustered" default-cache="default"> ... </cache-container>
2.4. Cache Modes
Data Grid Cache Managers can create and control multiple caches that use different modes. For example, you can use the same Cache Manager for local caches, distributes caches, and caches with invalidation mode.
- Local Caches
- Data Grid runs as a single node and never replicates read or write operations on cache entries.
- Clustered Caches
- Data Grid instances running on the same network can automatically discover each other and form clusters to handle cache operations.
- Invalidation Mode
- Rather than replicating cache entries across the cluser, Data Grid evicts stale data from all nodes whenever operations modify entries in the cache. Data Grid performs local read operations only.
- Replicated Caches
- Data Grid replicates each cache entry on all nodes and performs local read operations only.
- Distributed Caches
- Data Grid stores cache entries across a subset of nodes and assigns entries to fixed owner nodes. Data Grid requests read operations from owner nodes to ensure it returns the correct value.
2.4.1. Cache Mode Comparison
The cache mode that you should choose depends on the qualities and guarantees you need for your data.
The following table summarizes the primary differences between cache modes:
| Cache mode | Clustered? | Read performance | Write performance | Capacity | Availability | Capabilities |
|---|---|---|---|---|---|---|
| Local | No | High (local) | High (local) | Single node | Single node | Complete |
| Simple | No | Highest (local) | Highest (local) | Single node | Single node | Partial: no transactions, persistence, or indexing. |
| Invalidation | Yes | High (local) | Low (all nodes, no data) | Single node | Single node | Complete |
| Replicated | Yes | High (local) | Lowest (all nodes) | Smallest node | All nodes | Complete |
| Distributed | Yes | Medium (owners) | Medium (owner nodes) | Cluster capacity1 | Owner nodes | Complete |
- 1 Cluster capacity
Calculate cluster capacity for distributed caches as follows:
