This short video explains why companies use Hazelcast for business-critical applications based on ultra-fast in-memory and/or stream processing technologies.
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.
Now, deploying Hazelcast-powered applications in a cloud-native way becomes even easier with the introduction of Hazelcast Cloud Enterprise, a fully-managed service built on the Enterprise edition of Hazelcast IMDG. Can't attend the live times? You should still register! We'll be sending out the recording after the webinar to all registrants.
The data processing and computing platform Hazelcast has completely revamped its leadership team as it races towards aggressive growth targets. In a mix of promotions and new hires, the 12-year-old firm has made five new appointments:
John DesJardins, CTO of Hazelcast, the developer of an in-memory computing platform, has shared his thoughts with us about Intel Optane PMem, HBM and DDR5 DRAM.
Hazelcast today announced the appointment and promotion of key executives to its leadership team.
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As all online business becomes more competitive – within the same industry and in the broader realm of customer experience in web and mobile apps – low latency will continue to be a priority. So as a business, how can you ensure the highest performance from your systems when moving to the cloud?
In this podcast, John DesJardins, field CTO and VP solution architecture at Hazelcast, sat down with InfoQ podcast co-host Daniel Bryant. Topics discussed included: how in-memory data grids have evolved, use cases at the edge (IoT, ML inference), integration of stream processing APIs and techniques, and how data grids can be used within application modernization.
Edge computing has enormous potential to transform how companies leverage data to produce value.
Hazelcast today announced a new major feature and a number of enhancements to its in-memory data grid (IMDG), Hazelcast IMDG.
For this week’s episode, we spoke with Mike Yawn, a senior solution architect at Hazelcast, about the potential of in-memory computing to supercharge microservices and cloud native workloads.
Hazelcast today announced updates to its managed service that enables enterprises to simplify the delivery of multi-cloud capabilities to application modernization projects.
The latest release of Hazelcast's Jet event stream processing engine for AI and ML deployments of mission-critical applications adds new app development features designed to simplify the integration of an event-driven architecture into brownfield deployments to gain new functionality around real-time and in-memory processing.
Monolithic apps are difficult to evolve and are almost certain to be bogged down with years of technical debt. This is why software architects are turning to microservices.
We touched on the "where" aspect of the architecture - the physical locations and devices - in which each stage runs. However, there are several phases for edge-to-cloud deployment. So, let's dig in!
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