About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Azul and C24 Offer Compact In-Memory Storage Solution for Zing

Subscribe to our newsletter

Java specialist Azul Systems and messaging provider C24 Technologies have combined their expertise to deliver an in-memory storage solution compromising C24’s Simple Data Objects (SDO) message compaction technology integrated with Azul’s Zing Java virtual machine (JVM). The solution supports the Financial Products Markup Language (FpML), as well as FIX and ISO 20022 corporate actions messaging formats, and is designed, in the case of FpML to reduce the cost and improve the performance of OTC derivatives data storage. On a broader scale, it also addresses financial firms’ concerns about Java memory size and predictable performance.

Azul and C24 have worked together for some years using C24’s Complex Data Object storage technology on the Zing Java platform, which mitigates JVM issues such as jitter and garbage collection pauses. They are now moving forward with C24’s latest SDO message compaction technology that has a smaller footprint and can significantly reduce the hardware infrastructure cost of OTC derivates data storage. Performance improvement is achieved by giving Zing through simplified, yet fast access to the in-memory data.

Scott Sellers, Azul Systems co-founder and CEO, says: “C24’s SDO technology amplifies the benefits of Zing. By combining the technologies, the fears that many banks and investment houses might have concerning Java memory size and predictable performance are eradicated. C24 addresses big data memory use efficiency and Azul mitigates JVM-induced production issues.”

John Davies, chief technology officer and co-founder of C24, explains: “C24 SDO technology compacts traditional complex XML messages down to a tightly packed binary and wraps them with an ultra-efficient Java applications programming interface, in many cases reducing the memory footprint for stored data by well over 10-times. The data can be searched or queried with very little object creation, but the applications built on this technology run in Java and the only way to make that work with the sort of service level agreements our clients need is with a JVM like Zing.”

Azul and C24 expect both ultra-low latency and low latency traders to consider the solution for uses cases such as real-time big data analytics and real-time reporting. To date, two large banks have tested the solution and are moving it into production.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Are you making the most of the business-critical structured data stored in your mainframes?

Fewer than 30% of companies think that they can fully tap into their mainframe data even though complete, accurate and real-time data is key to business decision-making, compliance, modernisation and innovation. For many in financial markets, integrating data across the enterprise and making it available and actionable to everyone who needs it is extremely difficult....

BLOG

S&P Global Market Intelligence Wins A-Team Group’s AI In Capital Markets Best AI Solution for Research Summarisation Award

S&P Global Market Intelligence’s flagship data and analytics platform has won A-Team Group’s AI in Capital Markets Award for Best AI Solution for Research Summarisation. Data Management Insight spoke to Daniel Kim, senior director, head of digital engagement, data and research at S&P Global Market Intelligence and discusses the AI capabilities of its S&P Capital...

EVENT

TradingTech Summit New York

Our TradingTech Briefing in New York is aimed at senior-level decision makers in trading technology, electronic execution, trading architecture and offers a day packed with insight from practitioners and from innovative suppliers happy to share their experiences in dealing with the enterprise challenges facing our marketplace.

GUIDE

Regulatory Data Handbook 2025 – Thirteenth Edition

Welcome to the thirteenth edition of A-Team Group’s Regulatory Data Handbook, a unique and practical guide to capital markets regulation, regulatory change, and the data and data management requirements of compliance across Europe, the UK, US and Asia-Pacific. This year’s edition lands at a moment of accelerating regulatory divergence and intensifying data focused supervision. Inside,...