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.
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Since the first release of Hazelcast Jet Extension Modules in July, we’ve been focused on enhancing the set of extension modules that we have to make the integration easy between Hazelcast Jet and third-party data providers. Today, we are happy to announce the release of the following modules: MongoDB Connector MongoDB is a general-purpose, document-based, […]
The Open Banking initiative, also referred to as PSD2 (Payment Services Directive), is a textbook example of streaming technology applied to modern banking requirements. In this model, banks (primarily in Europe) are required to make their back-end systems for customer accounts and payment services available to other members of the financial payment ecosystem. While this […]
I’m sure you use caching somewhere in your system. This can be either to improve performance, reduce backend load, or to decrease downtime. Everybody uses caching. Caching is everywhere. However, in which part of your system should it be placed? If you look at the following diagram representing a simple microservice architecture, where would you […]
Introduction We all know that selecting the right technology for your business-critical systems is hard. You first have to decide what characteristics are most important to you, and then you need to identify the technologies that fit that profile. The problem is that you typically only get a superficial view of how technologies work, and […]
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 […]
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After releasing Hazelcast Jet 3.0 in May, we are happy to announce its first update, Hazelcast Jet 3.1. Hazelcast Jet is now an Apache Beam Runner Apache Beam is a framework for building distributed batch and stream processing applications over a unified API. The API itself is decoupled from the underlying execution implementation, making it […]
Unbounded, unordered, global-scale datasets are increasingly common in day-to-day business – IoT sensor network data streams, mobile usage statistics, large scale monitoring, the list is endless. Numerous applications seek the ability to quickly react to dynamic streaming data, as it is either a mandatory requirement or a competitive advantage. API Churn As a consequence, lots […]
Hazelcast IMDG is tightly integrated into the Kubernetes ecosystem thanks to the Hazelcast Kubernetes plugin. In previous blog posts, we shared how to use auto-discovery for the embedded Hazelcast and steps for scaling it up and down using native kubectl commands. In this post, we’ll focus on another useful feature, Rolling Upgrade. You can apply […]
The megatrends that have been driving the adoption of Hazelcast by the world’s largest organizations are now strikingly clear: Enterprises are awash in data and must leverage it for business advantage New applications must process stored and streaming data Application latency is the new downtime. The money is in the microseconds To meet these needs […]
At Hazelcast we take reliability very seriously. With the new CP Subsystem module, Hazelcast has become the first and only IMDG that offers a linearizable distributed implementation of the Java concurrency primitives backed by the Raft consensus algorithm. In addition to well-grounded designs and proven algorithms, reliability also requires a substantial amount of testing. We […]
The sidecar pattern is a technique of attaching an additional container to the main parent container so that both would share the same lifecycle and the same resources. You may think of it as a perfect tool for decomposing your application into reusable modules, in which each part is written in a different technology or […]
Last week, Hazelcast earned a coveted spot on the list of Red Herring’s Top 100 North America private technology companies. Make no mistake, there was nothing fishy or misleading about this honor. Ok, enough of the “red herring” puns. If you’re not familiar with Red Herring, it is a global media organization aimed at uniting […]
Artificial Intelligence (AI) as a concept has been around since the development of computational devices, as early as the creation of Turing machines during World War II. The term itself was first coined by University of Washington professor John McCarthy in 1956, and now, 60+ years later we see the actual commercialization of AI. Why […]
On Monday, Speedment and Hazelcast announced a partnership focused on accelerating application development when deploying an in-memory data grid alongside legacy databases. The following post was written by Speedment’s CTO, Per-Åke Minborg. What if you want to use a Hazelcast In-Memory Data Grid (IMDG) to speed up your database applications, but you have hundreds of […]
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