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!
The most common theme we hear about stream processing is how to make it easier. Many IT professionals understand the value that streaming data provides, but they still see a barrier to adoption due to the complexity of existing stream processing technologies.
Hazelcast products are all about simplifying scalable distributed in-memory data storage and processing with mission-critical reliability while providing best-in-class performance. This is especially critical in the rapidly expanding world of machine learning and artificial intelligence.
In this webinar, we’ll cover some of the new advanced features in Hazelcast Jet 4.0, and show you how Hazelcast Jet is a powerful building block which simplifies the development of real-time streaming and batch data analytics solutions. We’ll 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.
Joe Sherwin is a senior-level Solution Architect at Hazelcast® with 22 years of experience in the design, development, and implementation of application systems within multi-tier distributed computing environments. Working with clients such as Vanguard, Fannie Mae, Federal Reserve Bank, Citi Group, Bear Stearns, Fixed Income Clearing Corporation, Comcast Corp, Webster Bank, Gartner Group, The Hartford Life Company, IBM Global Services, Mass Mutual, Lincoln National Financial Corporation, Bank of America, and Barnes & Noble Online Group, Mr. Sherwin has been instrumental in the development of large-scale mission-critical E-commerce, insurance, and financial systems. He has experience architecting & implementing solution using CORBA, RMI, Java EE compliant distributed Object architectures, in-memory high transaction/low latency solutions using Hazelcast IMDG®, GemFire, Ehcache & Oracle Coherence, and solutions deployable on IaaS or PaaS platforms like Cloud Foundry, Amazon Web Services, Rackspace or Heroku.