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Financial Market Data

Hazelcast In-Memory solutions deliver against core requirements for financial services, across a broad range of use cases.

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Speed, when it really matters

Hazelcast In-Memory technology powers the most demanding financial services environments.

Speed, when it really matters

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.

Single Source of Truth
Single Source of Truth

Hazelcast provides a centralized API for use by front-, middle- and back-office systems to a single source of market data.

Domain Control
Domain Control

IMDG allows control over the Data Domain Model, cutting down on duplication of market data across multiple systems.

Access Control
Access Control

In-memory speed provides tighter control access to market data across the bank and provides a centralized point of authorization and audit.

Predictable Results
Predictable Results

In-memory allows for more predictable and accurately derived calculations with a single source of market data.

Drive user satisfaction to new levels

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.

Hazelcast In-Memory Computing Platform

Hazelcast In-Memory Computing Platform

The fastest in-memory solution for financial market data.

Hazelcast In-Memory Solutions

Hazelcast IMDG

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

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.

In-Memory Store and Cache

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

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.

Hazelcast Cloud

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.

Machine Learning and Artificial Intelligence

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.

Free Hazelcast Online Training Center

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.