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 guide is intended for software architects and developers who are planning or building systems requiring distribute infrastructure for application scalability and performance.
This white paper, written by Java Champion Ben Evans, provides an introduction for architects and developers to Hazelcast®’s distributed computing technology.
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.
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industry’s leading in-memory computing platform.
The in-memory speed you count on, with the convenience and scalability of cloud.
Lightweight, embeddable, powerful.
In today’s digital era, new systems are required that can deliver information with the time-sensitivity to meet rising business and consumer expectations. Hazelcast has already redefined high-performance processing for data at rest. Now, we are bringing that same level of performance to data in-motion, enabling a new breed of ultra-high-performance applications based on streaming data that allows you to process information faster, enable actions within shorter durations, and engage new data at the speed with which it is arriving.
Hazelcast Jet is built on the foundation of Hazelcast IMDG, the industry’s fastest in-memory data grid.
Hazelcast Jet is an application embeddable, distributed computing platform for fast processing of big data sets. The Hazelcast Jet architecture is high performance and low-latency-driven, based on a parallel, streaming core engine that enables data-intensive applications to operate at near real-time speeds.
Architecture & Features
Built on a distributed computing platform, Hazelcast Jet offers a parallel, low-latency core engine for data-intensive applications to operate at real-time speeds, while cooperative multi-threading architecture enables operation of thousands of jobs simultaneously.
Hazelcast Jet operates as shared application infrastructure or embedded directly in applications. It is ideal for microservices with a lightweight footprint, making data manipulation easy for developers and DevOps. Cloud and container ready.
One solution provides stream, batch, and RPC processing, with a variety of connectors to enable easy integration into data processing pipelines. Scaling, failure handling and recovery are all automated for ease of operational management.
Embed Hazelcast IMDG as an operational storage for enterprise-grade reliability and resilience, with high-performance integration that eliminates network transit latency and integration issues between processing and storage.
Big data processing at millisecond speed
Highly available and fault tolerant
Distributed, in-memory computation
Supports common data sources (Kafka, HDFS, Sockets, JMS, JDBC etc.)
Enables easy creation of custom sources
Contains scalable data storage with the clients Java, .NET, C++, Python, Node.js and Go
Embeddable for isolated and fully self-contained data-centric services
Elasticity for fault-tolerance and automatic scaling
Supports network discovery
Supports in-memory messaging
Enables low-latency analytics and decision making
Saves bandwidth and enhances privacy by processing data locally
Fully embeddable for simple packaging
Turnkey solution for using trained models in a production environment
Low-latency model execution environment
Apply real-time analytics to high-volume event data to make faster and better decisions
Integrate multiple applications to support multiple business functions
Build continuous analytics processing for enhanced revenue generation, smart resource allocation, improved customer service and other metrics
Hazelcast Jet reads a stream of telemetry data from ADS-B on all commercial aircraft flying anywhere in the world, typically 5,000 to 6,000 aircraft at any point in time. This data is filtered and aggregated, and then certain features are enriched and displayed in Grafana.
Hazelcast Jet uploads a stream of stock market pricing data from a Kafka topic into an IMDG map. Data is analyzed as part of the upload process, calculating the moving averages to detect buy/sell indicators.
The world's most advanced streaming core engine.
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Hazelcast Jet is the leading in-memory computing solution for managing streaming data across your organization. It is an application-embeddable, distributed computing solution for building high-speed streaming applications, such as IoT and real-time analytics. Hazelcast Jet is
built on the foundation of Hazelcast IMDG, the leading in-memory data grid and one of the top data stores for microservices deployments.
Hazelcast Jet® is an ultra-fast, application embeddable, third-generation stream processing engine for low-latency batch and stream processing. The Hazelcast Jet architecture is high-performance and low-latency-driven, based on a parallel, streaming core engine that enables data-intensive applications to operate at near real-time speeds.
Hazelcast Jet is built on top of Hazelcast IMDG®, the leading Open Source in-memory data grid, with millions of production systems running globally. Hazelcast Jet processing jobs take full advantage of the distributed in-memory data structures provided by Hazelcast IMDG.
Are you ready to make your machine learning algorithms operational within your business in real time? In this webinar, we will walk through an architecture for taking a machine learning model from training to deployment for inference within an Open Source platform for real-time stream processing.
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.