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!
Neil is a solution architect for Hazelcast®, the world's leading open source in-memory data grid. In more than 25 years of work in IT, Neil has designed, developed and debugged a number of software systems for companies large and small.
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In June 2019, we announced the inclusion of Hazelcast Jet as a runner for Apache Beam. Now it’s time for an example showing how it’s done. As a bonus, it’s not “Word Count.” IoT Data The data we will use is a series of 2,000 GPS points and time offsets: # Latitude, Longitude, Time-Offset 45.417,8.179,1629 45.417,8.178,1630 […]
This is an example showing one way you might connect to Hazelcast Cloud, and how you can harness its power for improved performance. As a problem, we’re going to calculate the spread of customer satisfaction, as the average doesn’t give enough insight. The example shows a custom domain model and server-side code execution. It shows […]
This is an example showing the use of YAML configuration, and populating a Hazelcast grid with data in JSON format that has been extracted from a traditional relational database. So the data goes from tables into “NoSQL” format. Hello YAML, Goodbye XML Hazelcast has many ways to be configured. Sensible defaults mean you don’t have […]
An step-by-step example to running Hazelcast on Kubernetes, the classic “Hello World” style beginners introduction. The sample includes instructions and screenshots for running on Mac. The process is essentially the same for Windows or Linux, although for Windows you will need a version that supports the appropriate networking (Windows 10 Professional not Windows 10 Home, […]
In this example. we’ll look at doing some analytics on an online shop to gain insights into customer behaviour. Background Most online shops follow a similar pattern in terms of the customer experience. Users are presented with a catalogue of products on a browser page or mobile application, and may make selections from these. Items […]
An example showing Hazelcast support for JCache 1.1. As a maintenance release to the JSR 107 Java Caching Specification, JCache 1.1 was released on 16th December 2017. This is now supported by Hazelcast, from release 3.9.3 onwards, released on 16th February 2018. This example allows you to build either version, to compare the differences. Mainly […]
Know “Go” but don’t know about “Hazelcast” ? Know “Hazelcast” but don’t know about “Go” ? This tutorial gets you going with both together, in a follow-along style, assuming you only know one of the two. Hello World Naturally, this is a simple example, “Hello World”, the bare minimum. We’ll start by installing the tools, […]
This example shows some of the newer features of querying, a way that joins can be achieved, and shows the pros and cons of partition aware routing. Although mainly an Hazelcast IMDG example, Hazelcast Jet puts in a guest appearance to implement the join. Background – Partitioning The most commonly used data structure in Hazelcast […]
Hazelcast provides distributed queues, an implementation of java.util.concurrent.BlockingQueue. However, an implementation of java.util.concurrent.PriorityBlockingQueue is not yet provided. In this example, we’ll see how to write this yourself, using Hazelcast’s SPI (Service Provider Interface). (Note: this is just an example, deliberately simplified. Attention is drawn to some extra steps to make this production quality.) Recap, “SPI“ […]
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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.