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!
Real-time, push-based propagation of changes to a Hazelcast IMDG cache from a system of record.
Hazelcast IMDG Striim Hot Cache ensures continuous synchronization between the cache and its underlying database, providing consistency with the system of record.
Real-Time, Push-Based Propagation
Striim’s Change Data Capture (CDC) functionality captures changes in underlying databases in real-time, and pushes them instantly to the cache, keeping it hot.
Change Data Capture Functionality
Striim recognizes which tables and key-values have changed, immediately captures these changes with its table and key, and using the Hazelcast IMDG Striim writer, pushes those changes into the cache.
CDC Wizard Speeds Deployment
Striim can configure the capture of change data from a variety of databases including Oracle, MS SQL Server, MySQL and HPE NonStop, and propagate that data to your Hazelcast IMDG cache.
Architecture
Reduces latency of propagation from a backend database into the Hazelcast cache to milliseconds, providing the flexibility to run multiple applications off a single database and keeping Hazelcast cache refreshes up to date while adhering to latency SLAs.
Recognizes which tables and key-values have changed, immediately capturing these changes with their table and key, focusing on incremental changes that minimize disruption to your existing workflows.
Allows changes to be applied to the specific domain model in the Hazelcast IMDG, including inserts, updates and deletes.
Supports Oracle, MS SQL Server, MySQL, HPE NonStop
Reduce the latency of propagation of data from a backend database into the Hazelcast cache to milliseconds.
Resources
In this video tutorial, Hazelcast cloud software engineer Rafal Leszko walks you through the steps to get Hazelcast running in embedded mode in a Kubernetes cluster.
Get up and running with the Hazelcast IMDG C# / .NET Client quickly with this easy to use reference card.
Get up and running with the Hazelcast IMDG Python Client quickly with this easy to use reference card.
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.
