Hazelcast Accelerates Financial Market Data Access for Investment Banking

Industry

Banking

Year Founded

1982

Product

Hazelcast Platform Enterprise

Competition in investment banking is highly dependent on timely financial market data. Maintaining these complex data feeds of “commodity” market data between systems has a high cost and can introduce complex project management burdens that stifle innovation. It is not unusual to find multiple development teams programming feeds for the same market data into their systems. Internally managed and centralized market data services have been a long-term goal of many investment banking organizations. Hazelcast provides the features to fulfill the various demands of a centralized Market Data System by:

  • Providing a centralized API for use by front-, middle- and back-office systems to a single source of market data.
  • Controlling the Data Domain Model and cutting down on duplication of market data across multiple systems.
  • Controlling access to market data across the bank and having a centralized point of authorization and audit.
  • Allowing for more predictable and accurately derived calculations with a single source of market data.
Why Most Datastores Fall Short…Why Hazelcast 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 a 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 ableto drastically narrow latency volatility to levels that are unachievable with NoSQL and RDBMS systems.

Existing infrastructures might not be cloud-ready to leverage the agility of the cloud.

Hazelcast has a cloud-native architecture that promotes agility by quickly leveraging the readily available resources in a cloud environment.

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, ROI 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.