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.
The value of enterprise-grade security, with the ease of cloud deployment and speed of in-memory
Industry-leading security with end-to-end TLS encryption, mutual authentication with X509 certificates, and roles-based authorization over data structures and actions, making security a seamlessly integrated component of your Hazelcast IMDG Enterprise application.
Architecture and Features
TLS / SSL communication for members and clients, and symmetric encryption for all socket-level communication, based on Java Cryptography Architecture.
JAAS-based authentication for pluggable identity verification, Socket Interceptor in order to add custom hooks to the cluster join operation and perform connection procedures, and TLS Mutual Authentication to ensure each communicating side proves its identity to the other.
Includes JAAS-based authorization for roles-based security, as well as a security interceptor that provides a callback point for every operation executed against the cluster.
Secure connections to external systems combined with security within the Hazelcast Jet cluster make the data pipeline secure end-to-end, using encryption, mutual authentication with X509 certificates, or pluggable mechanisms.
Machine learning (ML) brings exciting new opportunities, but applying the technology in production workloads has been cumbersome, time consuming, and error prone. In parallel, data generation patterns have evolved, generating streams of discrete events that require high-speed processing at extremely low response latencies. Enabling these capabilities requires a scalable application of high-performance stream processing, distributed application of ML technology, and dynamically scalable hardware resources.
See how the distributed compute features of Hazelcast can be used to build a rule engine for low-latency, high-throughput transaction processing.
Mainframe computers are used at many companies today, but the need for more cost-effectiveness is forcing changes. A popular strategy, mainframe optimization, enables lower mainframe costs due to the reduction in unnecessary MIPS. At the same time, it adds powerful new architectures related to cloud, microservices, and data streaming. An integration with IBM and Hazelcast […]
Whether you're interested in learning the basics of in-memory systems, or you're looking for advanced, real-world production examples and best practices, we've got you covered.