Hazelcast Cloud is an enterprise-grade in-memory computing platform deployed and managed by the Hazelcast CloudOps team. The service
is powered by Hazelcast IMDG Enterprise HD and leverages widely adopted technologies, such as Docker and Kubernetes, to provide dynamic orchestration and containerization. Hazelcast Cloud supports applications developed in some of the most common languages, including Java, Node.js, Python. Go, and .NET.
Hazelcast Cloud delivers enterprise-grade Hazelcast software in the cloud, deployed as a fully managed service. Leveraging over a decade of experience and best practices, Hazelcast Cloud delivers a high-throughput, low-latency service that scales to your needs while remaining simple to deploy. If you’re considering moving to the Cloud, or are looking for an easy ramp on deploying in-memory technology, this white paper on migrating in-memory to the cloud is an informative and helpful resource.
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.
Join this webinar on April 11th at 8:00 am PT / 11:00 am ET / 4:00 pm GMT 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!
Get a 30-day free trial.
Get started today with the
industry’s leading in-memory computing platform.
The in-memory speed you count on, with the convenience and scalability of cloud.
Future Grid works with several Australian utility companies to automate the processing of sensor and smart meter data which crosses energy networks. Their customers are collecting approximately 3 billion data points per day. In terms of daily post processing, this equates to 20 billion records as each record has multiple, individual data points –a massive scaling challenge. To make the most of this information, utility organizations need a real-time data aggregation and processing solution which enables them to make complex real-time decisions.
When Future Grid first tried to solve this problem, it used traditional relational databases. However, it soon became apparent traditional databases couldn’t cope with huge volumes of data in real-time, main issue being that they can’t execute algorithms against incoming data fast enough. Future Grid then decided to build its own solution combining Hazelcast IMDG® with Apache Cassandra’s persistence data store capabilities.
This case study tells the story of how Future Grid built its data platform and the primary use cases of their customers including: