Companies need a data-processing solution that increases the speed of business agility, not one that is complicated by too many technology requirements. This requires a system that delivers continuous/real-time data-processing capabilities for the new business reality.
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.
Setting up servers and configuring software can get in the way of the problems you are trying to solve. With Hazelcast Cloud we take all of those pain points away. Watch this webinar to learn how you can instantly fire up and then work with Hazelcast Cloud from anywhere in the world. With our auto-generated client stubs for Java, Go, Node.js, Python and .NET, we can have you connected and coding in less than a minute!
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The in-memory speed you count on, with the convenience and scalability of cloud.
While Hazelcast has run performance benchmarks against Oracle Coherence, the Oracle Technology Network License does not permit us to “disclose results of any program benchmark tests without Oracle’s prior consent.”
However, most people comparing Hazelcast IMDG® with Coherence will actually want to run a benchmark. With this in mind, we have a benchmark suite which we can share with you here.
Key Advantages of Hazelcast
While Hazelcast and Coherence share many similarities as true in-memory data grids, Hazelcast offers advantages that Coherence users should note.
Hazelcast includes features not available in Coherence, including support for multimaps, ring buffers, HyperLogLog, distributed atomic longs, distributed atomic refs, and distributed semaphores.
In addition to Java, C++, and C# (also supported by Coherence), Hazelcast supports Python, Node.js, Scala, and Go.
Hazelcast supports the near-cache and pipelining capabilities to boost performance.
Hazelcast supports reduced downtime via hot restart and rolling upgrades.
Hazelcast scales up by storing data in off-heap memory for higher capacity via the High Density Memory Store. Coherence relies on spilling over to disk, and requires running multiple server instances with a very small heap to mitigate garbage collection pauses.
Hazelcast is a cloud-native in-memory data grid that can be deployed anywhere. Hazelcast provides a lightweight technology in the form of a small JAR file that allows embedding in any Java application. Coherence deployment options are limited.
Whether you're interested in learning the basics of in-memory systems, or you're looking for advanced, real-world production examples and best practices, we've got you covered.
