A technical breakdown of overcoming retail constraints in high-frequency trading environments.
This case study details the deployment of a custom Python/C++ bridge designed to intercept live quote and trade data directly from the MetaTrader 5 (MT5)...
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A technical breakdown of overcoming retail constraints in high-frequency trading environments.
This case study details the deployment of a custom Python/C++ bridge designed to intercept live quote and trade data directly from the MetaTrader 5 (MT5) terminal, streaming it into a centralized PostgreSQL database.
By eliminating local data silos, this architecture enables sub-5ms sync speeds and provides a persistent, easily queryable SQL environment for proprietary quantitative models and enterprise-wide risk analysis.
Engineered by Diana Sterling | Systems Architecture & Data Engineering
Production Implementation: Pipswire Infrastructure
View the backend code and database schema: https://sites.google.com/view/diana-sterling/home
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