Why We Built It
Trading systems require more than speed. They demand precision, scale, and architectural resilience. To meet these needs, we engineered the EdgeCore Database Module, a high-performance, enterprise-ready data layer designed to store, transform, and serve time-series trading data at scale.
Built on PostgreSQL with TimescaleDB extensions, this module supports everything from real-time execution to historical strategy testing across millions of trades.
Enterprise-First Architecture
EdgeCore's dual-database architecture separates raw trade data from aggregated OHLCV candles, optimizing for both granularity and query performance. TimescaleDB hypertables allow efficient time-series operations, while our connection pooling infrastructure ensures consistent performance under heavy read/write load.
Key components include:
- TimescaleDB for hypertable-based time-series optimization.
- Trade and Candle Models to support both tick-level and timeframe-based storage.
- SQLAlchemy + psycopg2 dual interfaces for flexible querying.
- DatabaseConnectionManager to orchestrate pooled, fault-tolerant connections.
Performance at Scale
Designed for high-volume ingestion and access, the module supports:
- Real-time synchronization of tick and OHLCV data from exchanges like Binance.
- Resampling of raw trades into timeframes (e.g. 1m, 5m, 1h).
- Candle cleaning utilities to sanitize, fill, and de-duplicate records.
- Bulk insertions to improve efficiency and minimize write latency.
Data Pipeline & Flow
Ingestion: Exchange data is fetched and categorized into trades or OHLCV formats.
Transformation: Tick data is resampled into candles; incomplete or duplicate data is removed.
Storage: Trades and candles are stored in separate hypertables, indexed by timestamp and symbol.
Retrieval: The strategy engine accesses this data via optimized queries for backtesting and live trading.
Governance & Maintainability
- Database migrations are handled with precision using SQLAlchemy and a modular schema directory.
- Singleton access patterns ensure safe, shared access to persistent storage.
- Detailed logging and exception handling make debugging and rollback seamless.
Real-World Use Cases
- Enables historical and live trading for our institutional-grade EdgeCore engine.
- Supports real-time dashboards, AI model training, and strategic backtests.
- Powers Truso and AlgoEdge with fast, reliable access to multi-asset trade and candle data.
Why It Matters
This is more than a database. It’s the foundation for informed decision-making, accurate PnL tracking, and scalable trading automation. With EdgeCore’s Database Module, we bridge the gap between raw data and real intelligence—with speed, clarity, and enterprise-grade reliability.