Case Study: Trading Strategy achieves faster, more reliable real-time trading data with Timescale

Trading Strategy is a protocol for algorithmic trading of crypto assets in decentralized markets

Trading Strategy is a fintech and crypto platform that helps users build, test, and deploy quantitative trading strategies for the crypto market. As their real-time data volume grew across multiple exchanges, they struggled with scalability, slow query performance, and high latency in their legacy data infrastructure. To address these issues, they turned to Timescale and its time-series database capabilities.

Timescale implemented TimescaleDB to improve Trading Strategy’s data processing and storage. Features like automatic partitioning, compression, continuous aggregates, and hyperfunctions helped reduce latency, speed up queries, and handle real-time data more efficiently. The result was a more reliable and responsive platform, improved developer productivity, lower operational costs, and months shaved off MVP development time.

Trading Strategy

Mikko Ohtamaa

Chief Executive Officer