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!
Hazelcast® allows companies to dramatically speed up applications by reducing the query load on databases and using in-memory caching to return results faster. Integrating Hazelcast into an existing application requires modifying the application code – something that isn’t always possible due to cost, time, or lack of source code access.
Join us for our latest webinar as we demonstrate how Heimdall can be used to “Hazelcast-enable” any existing application without changing its code. Heimdall works at the JDBC-level intercepting queries and translating them into requests for Hazelcast cache objects. Heimdall allows an application developer or owner to dynamically create caching rules for SQL queries at run-time and leverage the dramatic performance improvements from memory-based caching. In just five minutes, any Java application can be transformed to use Hazelcast caching, as well as load balancing, high-availability with automated failover, SQL query transformation, routing, and performance visibility and analysis.
In This Webinar
Dr. Ramon Lawrence is VP of Engineering at Heimdall Data and an associate professor at the University of British Columbia, Canada. He has a Ph.D. in Computer Science with a research focus in database systems. His research and development activities have produced software systems for data virtualization and integration (http://heimdalldata.com/), querying NoSQL databases, including MongoDB, using SQL, and over 50 publications. He has performed database design projects for Fortune 500 companies including GE. Dr. Lawrence is a member of the ACM and senior member of IEEE.