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!
Hazelcast is used to accelerate the performance of transaction-based systems (i.e., ones that follow a “request-response” pattern) that have stringent requirements around high throughput and low latency. Such systems can encounter loads of millions of transactions per second, especially during load spikes. This means the system must run as quickly and efficiently as possible to deliver consistent response times at any load. The system must also offer elasticity to grow dramatically in anticipation of large seasonal load spikes.
This paper describes a high performance architecture based on Hazelcast Jet and Hazelcast IMDG.