Big Data at the Nexus of High Tech and Finance
For one client installation, Iris makes light work of more than five petabytes of data, and ingests and processes another five terabytes of real-time data every day. Sixty users—including algo-traders, compliance managers, risk controllers, quants, developers and operations/back office—are running real-time and historical queries across more than a thousand data query cores every day.
Since we switched to Iris, I spend my time driving alpha instead of waiting on developers. Speed is vital and Iris gives us the competitive edge.
Iris has become part of the foundation of our shop—a big data platform that’s accessible to every member of our team.
Having our firm’s data in one central “lake” allows our back and middle office the transparency we’ve been missing. Surveillance, cost analysis, you name it.
Build Alpha, not Infrastructure
Risk Management
P&L Attribution
Algos
Real-time Surveillance
Customer Analysis
Strategy Backtesting
Pairs Strategy Containers
Capital Consumption
Balance Sheet Support
Back-office Infrastructure
Fee Reconciliation
Signal Optimization
Custom Risk Control
Option Portfolio Dynamic What-ifs
Performance Correlations
Real-time Factor Exposures
Edge-to-Benchmark Analysis