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 looking to make it easier for organizations to benefit from machine learning alongside event streaming data, with the recent release of the Hazelcast Jet 4.0 update.
In-memory computing platform maker Hazelcast on Wednesday announced new support in its Hazelcast Jet event stream processing engine for artificial intelligence (AI) and machine learning (ML) deployments of mission-critical applications.
The latest release of the event stream processing engine, Hazelcast Jet, now helps enterprises unlock profit potential faster by accelerating and simplifying ML and artificial intelligence (AI) deployments.
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Hazelcast CEO Kelly Herrell sits down with John Furrier of theCUBE to talk about the role Hazelcast can play within the security space.
David Brimley, Financial Services Industry Consultant, Hazelcast, speaks to FinextraTV about what financial services firms are doing with machine learning and what firms should consider as they progress through their machine learning journey.
In-memory computing startups are hot at the moment. You don’t need to look further for evidence than Hazelcast, an eight-year-old San Mateo, California-based startup developing a speedy low-latency data processing platform.
Hazelcast, the leading in-memory computing platform that delivers radically fast application performance at scale, today announced the expansion of its Series D round due to over-subscribed interest from global investment entities.
Hazelcast today announced the expansion of its Series D round due to over-subscribed interest from global investment entities.
Drawing the curtains on the last 10 years, it will likely go down in history as the data decade. The massive digitization of every aspect of our business and society has created billions of fire hoses of new data being generated from everything from mobile devices to sensors to connected vehicles.
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