Case Study: MarketReader delivers real-time US market insights with TimescaleDB

MarketReader processes 3M trades/min with Timescale

MarketReader, a fintech startup providing US market trading insights, faced the challenge of processing an immense volume of real-time market data—averaging 3 million trades per minute—to detect unusual stock movements and deliver timely analytics to investors. Their need was for a high-performance database that could handle this scale for real-time ingestion and time-series analytics without adding architectural complexity. They selected TimescaleDB from vendor Timescale to address this.

Timescale implemented its cloud platform, Tiger Cloud, which utilizes TimescaleDB's hypertables for rapid data ingestion and continuous aggregates for statistical analysis. This solution allowed MarketReader to run all time-series analytics, statistical aggregation, and semantic vector search within a single PostgreSQL database. The results were a simplified architecture that eliminated the need for separate databases or specialized data pipelines, reduced operational overhead, and provided the performance and scalability required to deliver real-time insights without bottlenecks.

MarketReader