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.
Sr. Director of Technical Solutions, Dale Kim, will dive into Hazelcast’s in-memory data grid and event stream processing engine. He will also highlight some interesting and innovative use cases built by Hazelcast customers. After presenting the differences between the open source and enterprise editions of Hazelcast’s solution, Kim presents an architectural discussion of distributed computing using Hazelcast, including a look at data flows (streams and ad hoc requests), and where Hazelcast fits into enterprise application architecture. Hazelcast can ingest data from a variety of sources, including Kafka, MQ, IoT, enterprise applications, files, sockets, and database events, and output actionable content to these. Hazelcast acts as a system of record for distributed data in a cloud-first, memory-first, fast, reliable, and simplified way, providing low latency with resilience.
Recorded as part of Tech Field Day 23 on April 22, 2021.