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.
Technology modernization and re-platforming efforts are top-of-mind more than ever, especially in industries like retail banking that entail a demanding customer base. Challenges around customer service are growing due to higher expectations, so banks are turning to new technology approaches to help maintain success and gain competitive advantage.
Legacy systems have a proven track record in banking over the years, so the question is how to leverage everything that has worked so far, and combine new approaches to solve today’s new challenges. Exploration around which technologies to integrate is an important exercise that will enable banks to get ahead.
In this webinar, we’ll cover:
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.