Financial Services
Sub-200ms Data Processing for 500,000 Daily Market Events
A proprietary trading firm was missing time-sensitive opportunities because their platform took 1.8 seconds per event batch. We rebuilt the data pipeline. Processing now runs under 200ms.
The Challenge
What We Were Solving
The firm processed market data from four exchanges simultaneously but their existing platform averaged 1.8 seconds per event batch, making real-time analysis impossible. The database was a single MySQL instance handling both reads and writes with no separation. During high-volatility periods the system queued events, creating a data lag that cost the firm an estimated 420,000 GBP in missed opportunities over the previous year. The platform also lacked FCA-required audit trails for trade decisions.
The Solution
Our Strategic Approach
We re-architected the data pipeline with a write-optimised ingestion layer and a separate read-optimised analytics layer. Market events are processed through an in-memory queue before being written to partitioned tables designed for time-series queries. Read replicas serve the analytics dashboard with sub-second refresh. We implemented comprehensive audit logging that satisfies FCA requirements, recording every data point that influenced a trading decision. The system was load-tested with historical data from the highest-volatility trading day in the firm history.
What We Delivered
Deliverables
- Real-time market data ingestion pipeline processing 500K daily events
- Write-optimised storage with time-series partitioning
- Read replica architecture for analytics dashboard
- In-memory event queue for sub-200ms processing
- FCA-compliant audit trail for all trading decisions
- Performance monitoring with latency alerting
- Disaster recovery with 15-second RPO
- Historical data migration from legacy platform
How We Did It
Project Timeline
Data Flow Analysis
Mapped all exchange feeds, processing bottlenecks and latency sources. Established performance baselines and FCA audit requirements.
Pipeline Architecture
Event ingestion layer, in-memory queue, partitioned storage, read replica setup and analytics API.
Audit and Monitoring
FCA audit trail implementation, performance monitoring dashboard, latency alerting and disaster recovery testing.
Load Testing and Migration
Tested against peak historical data. Migrated 18 months of trading history. Parallel-run validation before cutover.
The Outcome
Measurable Results
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