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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The in-memory speed you count on, with the convenience and scalability of cloud.
Hazelcast In-Memory solutions deliver against core requirements for financial services, across a broad range of use cases.
Hazelcast In-Memory technology powers the most demanding financial services environments.
Financial services is dependent upon timely access to financial market data. Unfortunately, maintaining complex feeds of commodity market data between systems is costly and introduces complex project management burdens. That’s why the creation of internally managed and centralized market data systems have long been the goal of many financial services firms. Hazelcast IMDG makes it possible.
Hazelcast provides a centralized API for use by front-, middle- and back-office systems to a single source of market data.
IMDG allows control over the Data Domain Model, cutting down on duplication of market data across multiple systems.
In-memory speed provides tighter control access to market data across the bank and provides a centralized point of authorization and audit.
In-memory allows for more predictable and accurately derived calculations with a single source of market data.
25,000%
Reduction in time to accuracy
From seconds to microseconds
1.2 microseconds
Maximum application latency
Improved user experience
Exceed Expectations
Delight your traders and analysts by providing an instant response to rapidly changing market conditions.
Meet Burst Requirements
Move gracefully through extreme high-demand periods associated with the normal daily routine of financial market trading.
Improve Performance
Scale and improve your performance elastically, reducing hardware requirements and driving efficiency.
Why Most Data Stores Fall Short
Why Hazelcast IMDG is Ideal
Market data systems require the ability to onboard new data feeds quickly. RDBMS and NoSQL solutions typically require brittle manual integrations or expensive middleware to connect systems.
Hazelcast uses a single standard Java API and provides native language clients for Java, Scala, Node.js, Python, .NET, and C++, as well as for publishing an Open Client Network Protocol for building any other native language client needed.
Traditional relational databases such as Oracle or Microsoft use normalized data schemata that read-write from disk – not memory. This leads to poor application query performance resulting in unacceptable online customer experiences.
Hazelcast is a schema-less In-Memory data store, and is approximately 1,000 times faster than a RDBMS, achieving query and update times measured in microseconds for high volumes of data.
Integrating of multiple market data feeds quickly and easily without impacting existing throughput is a critical requirement for market data systems. Using an RDBMS, schema changes can impact systems and introduce narrow maintenance window requirements.
Hazelcast in contrast is a schema-less data store that is able to handle new data types without down-time.
Market data systems often used by trading desk systems demand low-latency access to data measured in microseconds.
Hazelcast’s unique in memory management is able to drastically narrow latency volatility to levels that are unachievable with NoSQL and RDBMS systems.
RDBMS and NoSQL are narrowly focused on being a datastore – integration with other systems, utilization of memory, and DevOps are secondary considerations often requiring purchase or integration of more software or hardware.
With Hazelcast IMDG, return on investment can be achieved in several areas, chiefly through reduced data integration effort, maximization of economies of scale in terms of memory utilization, and ongoing operational costs, both in terms of hardware and software.
The fastest in-memory solution for financial market data.
Hazelcast IMDG is the leading Open Source in-memory data grid (IMDG). IMDGs are designed to provide high-availability and scalability by distributing data across multiple machines. Hazelcast IMDG enriches your application by providing the capability to quickly process, store and access the data with the speed of RAM.
Hazelcast Jet is an application embeddable, distributed stream processing platform for building IoT and microservices-based applications. The Hazelcast Jet architecture is high performance and low-latency-driven, based on a parallel, distributed core engine enabling data-intensive applications to operate at real-time speeds.
High-Density Memory Store adds the ability for Hazelcast Enterprise HD IMDG to store very large amounts of cached data in Hazelcast members (servers) and in the Hazelcast Client (near cache), limited only by available RAM for extreme scale-up.
Stream processing is how Hazelcast processes data on-the-fly, prior to storage, rather than batch processing, where the data set has to be stored in a database before processing. This approach is vital when the value of information contained in the data decreases rapidly with age. The faster information is extracted from data the better.
The benefits of moving to the cloud are well known and applicable to virtually every industry. Hazelcast offers our customers the flexibility to deploy to the cloud on their terms, whether it's a dedicated cloud, on-premise cloud, hybrid cloud, or private cloud.
The speed of the Hazelcast In-Memory Computing Platform enables new levels of real-time predictive model servicing in support of delivering artificial intelligence solutions, as well as enabling real-time engineering and model retraining.
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.
