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The user has developed a stock market analytics platform using PostgreSQL, highlighting features like time-series storage and JSONB. They are inquiring about using Supabase for financial data applications, specifically regarding realtime subscriptions for live price streaming.
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.
The user describes a stock market analysis platform built on PostgreSQL, highlighting its architecture, database design, and data pipeline. They mention using features similar to Supabase, such as real-time updates and row-level security. The user is interested in Supabase's Realtime feature to simplify their current SSE-based price streaming.
The user shares their experience building a financial analytics platform, iGotFomo, using PostgreSQL as the primary database. They detail the architecture, data handling, and key patterns used in their system, including real-time data processing and machine learning feedback loops. The user seeks to compare approaches with others using PostgreSQL for similar analytical workloads.
The user shares a stock market platform, iGotFomo, that uses PostgreSQL for real-time financial data, tracking over 6,000 stocks. The platform includes various free tools and is built with Next.js, Express, and WebSocket. The user highlights the database architecture and the availability of the source code.