Global Investment Bank Speeds Up Its Equity Trading System with InterSystems Data Platform - InterSystems


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Global Investment Bank Speeds Up Its Equity Trading System with InterSystems Data Platform

A leading global sell-side investment bank with 50,000 employees and more than $1 trillion assets under management had conflicting requirements for their transaction management and analytics platform to reliably handle increasing trade order volumes while lowering infrastructure costs.

The globally distributed system had to be designed to accommodate billions of daily orders with sufficient headroom to handle unexpected spikes in orders during periods of market volatility, while concurrently servicing analytic queries from 250 applications across the organization.


• High Volume Multi-Workload Processing
• 3-5x Throughput Increase
• 10x Performance Improvement
• 75% Reduction in Operating Costs
• Zero Performance or Reliability Issues

Global Investment Bank

The bank had previously used an in-memory DBMS-based transaction management system, but had experienced performance and availability issues during periods of peak loads. The bank migrated the application to InterSystems Data Platform, resulting in 3-5x increase in throughput, 10x increase in performance, and 75% reduction is operational costs. In addition, the bank is now able to include more order data in the analytic queries, compared with their previous in-memory based system.

With the InterSystems-based implementation, there is no single point of failure, each functional component is linearly scalable, and it has successfully handled all trading days – including the 2008 financial crisis and the Flash Crash – with zero performance or reliability issues.

Basing their equities trading system on InterSystems Data Platform is providing the global investment bank with the performance and capacity they need to meet the challenges presented by strong growth now, and well into the future.

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InterSystems Financial Services

Successful financial services organisations today must be able to simultaneously process transactional and analytical workloads at high scale. Read more here
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