This short video explains why companies use Hazelcast for business-critical applications based on ultra-fast in-memory and/or stream processing technologies.
Stream processing is a hot topic right now, especially for any organization looking to provide insights faster. But what does it mean for users of Java applications, microservices, and in-memory computing?
In this webinar, we will cover the evolution of stream processing and in-memory related to big data technologies and why it is the logical next step for in-memory processing projects.
Now, deploying Hazelcast-powered applications in a cloud-native way becomes even easier with the introduction of Hazelcast Cloud Enterprise, a fully-managed service built on the Enterprise edition of Hazelcast IMDG. Can't attend the live times? You should still register! We'll be sending out the recording after the webinar to all registrants.
Hazelcast has performed a number of performance benchmarks against Redis providing a core set of conclusions:
Our latest performance benchmark tests compare Hazelcast Enterprise 3.12 versus Redis Open Source 5.0.3. The results are similar to past benchmarks, highlighting Hazelcast’s performance advantage at scale. The table below shows some key performance metrics:
Hazelcast Enterprise 3.12
Redis Open Source 5.0.3
Throughput using 128 threads1
Throughput using 64 threads2
Throughput as load scaled3(see chart below)
Scaled linearly to 128 threads
Maxed out at 32 threads, performance degraded beyond that
1 In the Hazelcast Responds to Redis Labs’ Benchmark report.
2 In the Hazelcast IMDG Enterprise 3.12 vs Redis Open Source 5.0.3 report.
3 In the Hazelcast Responds to Redis Labs’ Benchmark report.
See the results of the latest benchmarks and read more about the background of these tests by visiting the two reports on separate benchmark runs:
We’ve compared Hazelcast and Redis performance on many occasions. See our two previous published benchmarks:
Contact us now to add Hazelcast In-Memory Data Grid to your business.