Skip to content
Effectuez une recherche pour en savoir plus sur les produits et solutions InterSystems, les offres d'emploi, etc.

Surviving in the New, High-Speed World of Financial Services

High Speed World of Financial Services

Increasing trade volumes and periods of high market volatility can create significant challenges for financial services firms' data management infrastructure.

This is especially true in front- and middle-office applications in capital market firms. Sell-side firms in particular can experience extremely high transaction volumes, since they partition already high volumes of incoming orders into even more orders for execution. At the same time, they must support a high volume of concurrent analytic queries to provide information on order status, risk management, compliance, surveillance, and other key metrics, for internal and external clients. This requirement for multi-workload processing at very high scale — coupled with the need for the highest levels of performance and reliability, and a low total cost of ownership — has been difficult to achieve.

A leading global bank improved data throughput 500%, reduced latency by 1000%, and lowered operating costs by 75% compared with its previous in-memory DBMS, all without a single incident since its initial implementation.

Compounding the challenge is the fact that transaction volumes not only grow incrementally and within expectations, but also often spike dramatically in response to unexpected world events. Recent examples include the 2008 financial crisis, 2010 Flash Crash, devaluation of China’s currency in 2015, Brexit, trade wars, and many other political events.

The data platform underlying a firm’s real-time and near real-time front- and middle-office applications is a critical component of its technology infrastructure. The applications must be extremely reliable and highly available — able to withstand both normal transaction volume growth and the extreme spikes that can occur during periods of market volatility, without incident.

A failure, or even just a slowdown, of the underlying data management infrastructure can have severe consequences for a firm. For example, with in-memory database technologies, it can take minutes or hours to rebuild the database and resume normal operations after a failure. In the meantime, the firm’s ability to process additional trades and provide order status and other critical information is compromised, and financial losses mount.

Even a slight delay or outage can cause significant financial losses and impact a firm’s reputation. One major bank recently reported a loss of $100,000 for each minute that its order management system was down.

Example: Order Management System

An order management system is a critical component of a bank’s technology platform. It must record all orders originating from both clients and internal sources, ensure proper routing and execution of the orders, maintain the state integrity of each order (for example, if an order is only partially filled), record and properly allocate all trade executions, and preserve all data, while concurrently processing analytic workloads on the trade data. It is absolutely mission-critical; it cannot slow down, drop trades, or go dark, regardless of market volume or volatility.

To successfully handle growth and volatility without performance or availability issues, a data platform must balance transactional workloads with the concurrent analytic demands of downstream applications. Financial services organizations must be able to process millions of incoming messages per second while simultaneously supporting thousands of analytic queries per second from hundreds of systems that must report on the state of orders while performing other queries.

Traditional operational databases are too slow to accommodate the high throughput and data-access rates required. And in-memory databases alone are not sufficient for many applications for a number of reasons:

  • Scale limitations. Because the data in an in-memory database is stored in main memory, the working data set is limited by the available amount of memory. As a result, as data volumes and/or analytic query workloads increase, at some point both the transaction processing and the analytic queries will slow or stall.
  • System downtime. Because the data is stored in memory, if the database server fails, the data that is resident in memory on that server is lost. Some in-memory database systems offer persistence through mirror databases, replication, and other approaches. These techniques can affect ingest performance and cost, and increase maintenance complexity. For databases where the data is stored in files and transaction logs, the recovery effort involves rebuilding the database using the logs, checkpoint files, and other backup data. This is a time-consuming process, during which time the bank’s ability to process orders is compromised, resulting in revenue losses and other penalties to the business.
  • High costs. Scaling in-memory systems is expensive. And because servers have hard memory limits, scaling in-memory databases beyond these limits requires firms to purchase additional nodes to sustain normal operations and allow headroom for unexpected volatility, which increases costs.

A New Approach

Fortunately, there is a new approach that delivers performance equal to or better than that of an in-memory database, but with none of the compromises. InterSystems IRIS® data platform provides the durability and reliability of a traditional operational database, but with better resource efficiency and a lower total cost of ownership. Unlike both in-memory and traditional operational databases, it is optimized for extremely high performance for both transactions and concurrent analytical processing, without incident or performance degradation, even during periods of extreme market volatility.

This data platform delivers fast transactional and analytic performance without sacrificing scalability, reliability, or security. It handles relational, object, document, key-value, and multi-dimensional data in a common, persistent storage tier, without any replication of the data.

Unlike traditional in-memory databases, since the data is always stored on disk in a format optimized for random access, there is never a need to rebuild the database.

The data platform offers a unique set of features that makes it highly attractive for mission-critical transactional-analytic applications, including:

  • High performance for transactional workloads, with built-in persistence,
  • High performance for analytic workloads,
  • Consistent high performance for concurrent transactional and analytic workloads at scale, and
  • Lower total cost of ownership compared with in-memory technologies.

Conclusion

The high-speed world of financial services presents some of the most demanding requirements for technology infrastructures.

Fortunately, there is a technology that can meet these seemingly conflicting requirements: processing both transactions and analytic queries concurrently, at very high scale, with the highest levels of reliability even when markets spike, and with a low total cost of ownership.

For more information about InterSystems IRIS data platform, visit InterSystems.com/Financial.

InterSystems is the information engine that powers some of the world’s most important applications. In healthcare, business, government, and other sectors where lives and livelihoods are at stake, InterSystems has been a strategic technology provider since 1978. InterSystems is a privately held company headquartered in Boston, Massachusetts (USA), with offices worldwide, and its software products are used daily by millions of people in more than 80 countries.

 

RELATED TOPICS

Autres Ressources Que vous Pourriez Apprécier

09 Oct 2025
Fact Sheet
InterSystems IRIS and IRIS for Health Managed Service assists customers that want to focus on their core business and innovate faster, and have InterSystems manage all of the provisioning, operation, and maintenance of our InterSystems IRIS software and the supporting cloud infrastructure.
09 Oct 2025
IDC MarketScape
InterSystems est positionné en tant que leader dans l'IDC MarketScape pour la région EMEA. Plateforme de données de santé pour les fournisseurs 2025 Évaluation des fournisseurs
08 Oct 2025
Market Note
This TabbFORUM report explores how AI is moving from cool novelty to core infrastructure, what’s working in production today, and where the next wave of adoption will determine lasting competitive advantage.
03 Oct 2025
Exécution des commandes
InterSystems Supply Chain Orchestrator unifie les données issues de milliers de sources disparates, vous offrant une visibilité en temps réel et des recommandations prescriptives sur l’ensemble de votre chaîne d’approvisionnement.
03 Oct 2025
Optimisation des stocks
InterSystems Supply Chain Orchestrator unifie les données provenant de milliers de sources pour vous aider à anticiper les perturbations, à faire des prévisions plus intelligentes grâce à l'IA et à prendre les bonnes décisions en temps réel.
03 Oct 2025
Industry Insights
GenAI, Large Language Models, and Natural Language Processing are Fundamentally Transforming Healthcare
02 Oct 2025
HIMSS Market Insights
HIMSS Market Insights conducted this research, sponsored by InterSystems, in April and May 2025 among leaders in MedTech organizations to understand their perspective on integration solutions and efforts. We looked at:
29 Aug 2025
Les plateformes, moteurs de la transformation numérique en santé
Publié dans Clinicum Romandie, numéro 2/2025
27 Aug 2025
Supply Chain
Gagnez en visibilité intelligente sur votre supply chain Les chaînes d’approvisionnement font face à des disruptions constantes : événements météorologiques, tensions géopolitiques, pénuries de main-d’œuvre ou encore problèmes de capacité. L’intelligence décisionnelle peut aider en exploitant l’IA, le machine learning et les simulations pour prédire les résultats, évaluer différents scénarios et recommander la meilleure action afin de surmonter ces perturbations.
25 Aug 2025
InterSystems IRIS for Health™ en tant que référentiel et entrepôt de données indépendant
Un référentiel de données cliniques permet le traitement des données de santé en dehors du système de dossiers patients informatisés (DPI). Téléchargez le livre blanc pour en savoir plus.

Passez à l'étape suivante

Nous serions ravis d'échanger avec vous. Remplissez les champs suivants et nous vous recontacterons.
*Champs obligatoires
*Champs obligatoires
*Champs obligatoires
*Champs obligatoires
** En cochant cette case, vous consentez à recevoir des actualités, des mises à jour et toute autre information à objectif marketing liés aux produits et événements actuels et futurs d'InterSystems. En outre, vous consentez à ce que vos coordonnées professionnelles soient saisies dans notre solution CRM hébergée aux États-Unis, mais conservées conformément aux lois applicables en matière de protection des données.