Advanced CP Subsystem
Build applications that depend on strongly consistent data with in-memory speeds and mission-critical resilience.
Strongly consistent data in an ultra-fast and resilient platform
Ensure accurate data for your applications in a fast, fault-tolerant, distributed system by using the Hazelcast implementation of the Raft Consensus Algorithm.
- Get the correct up-to-date values even upon hardware failures that might disrupt the proper sequence of data updates
- Reduce the consistency/performance trade-off with in-memory speeds
- Add an additional level of fault tolerance by writing consistent values to disk for fast recovery
- Fast, resilient, and consistent data ensures no errors and surprises due to stale data
- Raft Consensus Algorithm ensures data is consistent across all participating members
Features
Strong Consistency
Depend on strongly consistent data as a more reliable alternative eventually consistent data.
High Performance
Get the highest performance in your applications so you don’t make a significant trade-off to gain the benefits of strong consistency.
Mission-Critical Resilience
Ensure the resilience you need to run mission-critical applications that rely on consistent data using replicas as well as durable on-disk storage “CP Subsystem Persistence”.
Simple API
Write applications that leverage a wide variety of strongly consistent data types, including key/value stores “maps”, in an easy-to-use API.
Hazelcast Training: Strong Data Consistency. Explore how the Hazelcast Platform CP Subsystem ensures guaranteed data consistency.
Related Resources
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