Hazelcast IMDG is a clustered, in-memory data-grid that manages application data and distributes processing using in-memory storage and parallel execution for breakthrough application speed and scale. In this Quick Start Guide, learn what an in-memory data grid can be used for, how to do simple query operations with Hazelcast IMDG, what sharing means with Hazelcast, and more. This paper is intended for software architects and developers who are planning or building systems requiring distribute infrastructure for application scalability and performance.
Microservices, as an architectural approach, has shown a great deal of benefit over the legacy style of monolithic single applications. Nevertheless, microservices are not without their drawbacks. The purpose of this white paper is to show first steps for using Spring Boot and Hazelcast IMDG® contribute to the microservices landscape, enhancing the benefits and alleviating some of the common downsides.
This white paper, written by Java Champion Ben Evans, provides an introduction for architects and developers to Hazelcast®’s distributed computing technology.
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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.
This white paper introduces you to the domain of stream processing covering these topics:
This paper is intended for software architects and developers who are planning or building system utilizing stream processing, fast batch processing, data processing microservices or distributed java.util.stream.