Hazelcast IMDG is a clustered, in-memory data-grid that manages application data and distributes processing using in-memory storage and parallel execution for breakthrough application speed and scale. In this Quick Start Guide, learn what an in-memory data grid can be used for, how to do simple query operations with Hazelcast IMDG, what sharing means with Hazelcast, and more. This paper is intended for software architects and developers who are planning or building systems requiring distribute infrastructure for application scalability and performance.
Microservices, as an architectural approach, has shown a great deal of benefit over the legacy style of monolithic single applications. Nevertheless, microservices are not without their drawbacks. The purpose of this white paper is to show first steps for using Spring Boot and Hazelcast IMDG® contribute to the microservices landscape, enhancing the benefits and alleviating some of the common downsides.
This white paper, written by Java Champion Ben Evans, provides an introduction for architects and developers to Hazelcast®’s distributed computing technology.
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This is a comparison between a Redis 3.2.8 cluster and a Hazelcast IMDG® 3.8 cluster.
Read our previous benchmark here >>
Hazelcast IMDG was up to 56% faster than Redis.
Note that near cache was disabled for Hazelcast®.
As you can see from our previous benchmark, enabling near cache makes us 5 times faster.
Hazelcast IMDG was up to 44% faster on puts.
We think Hazelcast IMDG is faster because of the following design differences:
This is the second performance test we have done where Hazelcast IMDG beats Redis. See our earlier Redis 3.0.7 vs Hazelcast IMDG 3.6 Benchmark. We have extended our performance lead over Redis with Hazelcast IMDG 3.8.
3 physical boxes dedicated to cluster members, 5 physical boxes for clients.
Hazelcast IMDG uses a map configured with HD in memory format and async backups, by default read from backups is disabled.
Redis master Slave replication is async, by default Redis allows read from backups.
<native-memory allocator-type="POOLED" enabled="true">
<size unit="GIGABYTES" value="100" />