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 Jet is a distributed stream processing engine that supports exactly-once semantics even in the presence of cluster member failures. This is achieved by snapshotting the internal state of the processors at regular intervals into reliable storage and then, in case of a failure, using the latest snapshot to restore the state and continue. However, […]
Hazelcast Jet allows you to distribute stream processing over several cluster nodes. While it comes with several out-of-the-box sources to read from (Hazelcast IMap, JMS, JDBC, etc.), and sinks to write to, there’s no Java 8 streams source. In this post, we are going to create an adapter to bridge this gap. A Look at […]
Given the unprecedented scale of COVID-19, we would like to take a moment to share how Hazelcast is navigating the situation to maintain our commitment to you and your customers while protecting the health and safety of our team members. Our responsibility. With more than 130 employees across 21 countries, we’re a highly distributed workforce […]
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Today is PI DAY! Obviously, Pi has rather more than 2 decimal places. To have some fun, let’s use Jet to drive multiple Python workers to calculate Pi with increasing accuracy. A tiny bit of mathematics Pi is the ratio of a circle’s radius to its circumference. It’s 3.14. It’s 3.1416. It’s 3.14159266 or whatever. It […]
Machine learning projects can be split into two phases: Training Inference During the training phase, data science teams have to obtain, analyze and understand available data and generalize it into a mathematical model. The model uses the features of the sample data to reason about data it has never seen. Although it can be completely […]
We’re happy to introduce Hazelcast Jet 4.0 and its new features. This release was a significant effort and featured 230 PRs merged which makes it one of our biggest releases in terms of new features. Distributed Transactions Jet previously had first-class support for fault tolerance through implementation of the Chandy-Lamport distributed snapshotting algorithm, which requires […]
A lot of a developer’s work is about transforming and aggregating data: Increasing the quantity of a product in a shopping cart Applying VAT on the price of a product Computing the price of a shopping cart Etc… Sometimes, one needs the features of a full-fledged stream processing engine, such as Hazelcast Jet, sometimes not. […]
Among the many capabilities of an in-memory data grid (IMDG), caching is one of the most well-known and used. However, as its name implies, data resides in memory. The memory is of finite capacity. In order not to put more data than memory can handle, we must decide how to curate it. Hazelcast comes with […]
I joined Hazelcast in January 2014 as employee number 12. At that time Hazelcast 3.1 was the current version. Since then, about every 7-8 months we have done a “minor” release, the latest of which is 3.12. Minor in the sense that they maintained binary compatibility. We added many features and improved many aspects of […]
Today, Hazelcast is moving to a three-license software licensing model: Apache 2.0 for the core of our systems, consistent with our history A new source-available Hazelcast Community License A proprietary license for selected Enterprise operational features, consistent with our history The license model change will have no impact on users and is only intended to […]
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