Strategies for Enhancing Data Engineering for High Frequency Trading Systems

This paper examines essential techniques and best practices in data engineering that improve the efficiency and speed of high-frequency trading (HFT) systems. It discusses strategies for optimizing data ingestion, storage architectures, real-time processing, and data analytics, with a strong focus on minimizing latency and maximizing throughput. The role of hardware acceleration, including FPGA and GPU-based solutions, is also explored as a means of achieving performance improvements. HFT systems demand advanced data engineering methods to process large volumes of market data at ultra-low latencies. Optimizing data pipelines, storage, and processing infrastructure is key to achieving the high performance required for these systems.