Caching with Hazelcast
Last updated August 17, 2024
Hazelcast provides powerful caching capabilities, allowing you to significantly improve the performance of your applications by storing frequently accessed data in memory. This guide explores Hazelcast's caching features, enabling you to optimize your application's response times and reduce the load on your backend systems.
Hazelcast Caching Features
- Distributed Caching: Hazelcast's caching capabilities extend across multiple nodes in a cluster, making data easily accessible to all nodes. This allows you to scale your cache capacity and ensure high availability in the face of node failures.
- Memory-Based Performance: Hazelcast caches data in memory, providing significantly faster access compared to disk-based storage. This leads to faster response times for frequently accessed data, improving the overall user experience.
- Eviction Policies: To manage cache size and prevent memory exhaustion, Hazelcast provides various eviction policies that automatically remove entries based on their access patterns. Some common eviction policies include:
- Least Recently Used (LRU): Evicts the least recently used entries first.
- Least Frequently Used (LFU): Evicts the entries that have been accessed least frequently.
- Time-to-Live (TTL): Evicts entries after a specified time period.
- Max-Size: Evicts entries when the cache reaches a defined maximum size.
- Cache Loading: Hazelcast offers mechanisms to automatically load data into the cache when a requested entry is not found. This ensures that data is efficiently loaded into the cache as needed.
Implementing Caching with Hazelcast
1. **Configure the Cache:** Use the `HazelcastInstance` to create an `IMap` and configure its caching properties.
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