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 first generation of microservices was envisioned as stateless request-response endpoints. But it’s now clear that microservices must often maintain some state. For example, microservices tasked with running machine learning models or engaged in statistical classification must maintain the state of their models and their parameter weights. This brings us to one of the biggest challenges—where is that state stored? Options like RDBMSs are too slow, do not scale, and have inflexible schema models. Distributed in-memory caching, however, is the only widely adopted enterprise technology that offers high speed, scalability, and dynamic schema evolution.
In this webinar, we will discuss:
Dale Kim is the Senior Director of Technical Solutions at Hazelcast and is responsible for product and go-to-market strategy for the in-memory computing platform. His background includes technical and management roles at IT companies in areas such as relational databases, search, content management, NoSQL, Hadoop/Spark, and big data analytics. Dale holds an MBA from Santa Clara and a BA in computer science from Berkeley.
Lucas is a Principal Solutions Architect at Hazelcast, where he helps Hazelcast’s most demanding customers architect, design, and operationalize enterprise software systems based around Hazelcast IMDG and Jet. Before joining Hazelcast, Lucas held similar positions at GigaSpaces and GridGain, giving him a uniquely broad and deep understanding of the in-memory platform space. Lucas holds a B.S.E. in computer science from the University of Michigan.
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