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Operating Streaming Applications in the Cloud

Webinar
| Video
| 60 minutes

In this webinar, we will present the tools that Hazelcast Jet brings to the table when it comes to operating long-running streaming applications in the cloud.

Hazelcast Cloud Product Brochure

Brochure
| PDF
| 3 pages

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 Jet for Hazelcast IMDG Users

Webinar
| Video
| 60 minutes

Hazelcast Jet® is a 3rd generation stream processing engine that adds advanced data processing capabilities to Hazelcast IMDG®. Jet makes it simple to build distributed, fault-tolerant data processing pipelines on top of Hazelcast IMDG and provides 500% performance increase over similar processing done with Apache Spark. Just like Hazelcast®, it can be embedded into your application or run as standalone.

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How You Can Quickly and Effortlessly Integrate Your Database with Hazelcast

Webinar
| Video
| 60 minutes

Hazelcast Auto Database Integration (Auto DBI) is a highly efficient time-saving tool for working with databases. It streamlines the development of Hazelcast applications by generating a Java domain model representation (POJOs and more) of the database, allowing companies to be productive with Hazelcast in no time

Hazelcast Jet Briefing for the Financial Services Community

Webinar
| Video
| 60 minutes

Performant, elastically scalable and resilient, Hazelcast Jet has been used extensively in Financial services for a wide range of real-time use cases.  In this webinar Hazelcast Jet product manager, Vladimir Schreiner will provide an overview of Hazelcast Jet, and how it is used at some of the world’s leading banks and credit card providers.

Auto Database Integration

Video
| Video

Watch this one minute demo on how to streamline the development of Hazelcast applications. Learn how you can automatically generate the Java domain model from the database and save a lot of time.

The Crucial Role of Streaming Technology for Business

Whitepaper
| PDF
| 11 pages

This white paper walks through the business level variables that are driving how organizations can adapt and thrive in a world dominated by streaming data, covering not only the IT implications but operational use cases as well.

Hazelcast IMDG Deployment and Operations Guide

Guide
| PDF
| 66 pages

The Hazelcast IMDG® Deployment and Operations Guide provides an introduction to the most important aspects of deploying and operating a successful Hazelcast® installation. This edition is current with Hazelcast IMDG version 3.11. In this guide, you’ll learn about different approaches to topologies, advantages and disadvantage of various types of architecture and how to configure Hazelcast for optimal success. You’ll learn how to plan for lifecycle events to ensure high uptime and smooth operation. This guide also covers Hazelcast-specific optimization considerations to keep in mind when preparing for a new Hazelcast deployment. You’ll learn how to determine cluster size and how to authenticate cluster members and clients, as well as how to deploy and scale a Hazelcast cluster while ensuring failure detection and recovery. Moreover, you’ll learn about license management and how to report issues to Hazelcast. Download the guide to get started now.

SigmaStream and Hazelcast Helps the Energy Industries Save Millions

Case Study
| PDF
| 4 pages

Stream processing is the new critical application for today’s always on, always available digital ecosystem. While stream processing can cover a wide range of applications (healthcare, IoT, payment processing, etc.), Hazelcast’s stream processing engine – Jet – has had an interesting and unusual deployment in the oil and gas drilling domain, with spectacular results. SigmaStream, […]

Auto Database Integration

Case Study
| PDF
| 2 pages

This use case outlines how a logistics company has cut maintenance costs and drastically reduced the overhead of setting up new applications. Hence, time to market is shortened by streamlining the process of keeping the data model of the in-memory data grid in sync with the data sources.

Operating Streaming Applications in the Cloud

Webinar
| Video
| 60 minutes

In this webinar, we will present the tools that Hazelcast Jet brings to the table when it comes to operating long-running streaming applications in the cloud.

A Reference Guide to Stream Processing

Guide
| PDF
| 13 pages

The goal of streaming systems is to process big data volumes and provide useful insights into the data prior to saving it to long-term storage. The traditional approach to processing data at scale is batching; the premise of which is that all the data is available in the system of record before the processing starts. In the case of failures the whole job can be simply restarted. While quite simple and robust, the batching approach clearly introduces a large latency between gathering the data and being ready to act upon it. The goal of stream processing is to overcome this latency. It processes the live, raw data immediately as it arrives and meets the challenges of incremental processing, scalability and fault tolerance.