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!
Traditional data warehousing has long used batch jobs to move, load and transform data for decision making. But as data volumes rise and the velocity of business grows, more organizations are opting to move and process data in real-time or near real-time. Batch processing is giving way to mini-batches fueled by replication and change data capture as well as stream processing in which events are captured, processed, and analyzed as they happen.
Many companies today have a mix of batch, mini-batch, and stream-based processing. The question is whether organizations should embrace streaming as the default mode of data acquisition? Several vendors are now pitching streaming-first architectures and extolling the benefits of processing data in real-time. This webinar will explore the pros and cons of a streaming-first architecture and examine industry trends in its adoption.
You Will Learn: