Supabase | The Open Source Firebase Alternative

Built a Stock Market Platform with PostgreSQL + Real-Time Data Pipeline

Database

Realtime

Express

Next.js

JavaScript

Stock Market Data Platform Architecture

Sharing a platform we built that processes real-time stock market data for 6,000+ symbols using PostgreSQL as the core data store.

PostgreSQL Schema Design

stock_ohlc_data - Time-series OHLCV with hourly sync (5yr history, 290 stocks deep backfilled)
options_chain_data - Full options chains for 99 Tier 1 symbols
convergence_alerts - 8 detector types with JSONB raw_data
earnings_intelligence - AI-generated analysis with UNIQUE(symbol, earnings_date, analysis_type)
strategy_episodes - ML feedback loop with 782+ measured trades

Real-Time Pipeline

13 WebSocket connections → 6,000+ symbols
    ↓
5-source price aggregator (median outlier rejection)
    ↓
PostgreSQL (INSERT ON CONFLICT UPDATE)
    ↓
BullMQ job queue (background sync)
    ↓
Express API → Next.js SSR

Key Decisions

PostgreSQL over TimescaleDB - Simpler ops, good enough with proper indexing
JSONB for flexible signal data - Each detector stores different schemas
Local-only backtesting - All data pre-cached, zero external API calls during backtests
IC-weighted signal scoring - 12 signals with dynamic weights from ML feedback

Free Tools

Stock Screener - 6,000+ stocks with convergence signals
Market Pulse - Live dashboard
Stock Calculator - ROI & options P/L

How to help

The user shares their experience building a stock market platform using PostgreSQL and a real-time data pipeline. They describe the architecture, including schema design and key decisions like choosing PostgreSQL over TimescaleDB and using JSONB for flexible data storage. The platform processes data for over 6,000 symbols and includes tools like a stock screener and live dashboard.

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