As a FinTech tech lead, I’ve onboarded several real-time market data feeds for US equities. The performance gap between a well-optimized API and a generic one can be over 200ms — enough to turn a profitable strategy into a loser. Here’s how I evaluate them, complete with code. Breaking Down Latency Latency comes from three main places: Transport: HTTP adds overhead; WebSocket delivers push in real time. Location: Servers near exchange data centers send data faster. Serialization: JSON parsing slows you down at scale. Mandatory Metrics Metric Target End-to-end latency < 80ms median Throughput ≥ 1500 tick/s under load Packet loss < 0.001% Messages must be sequenced and in order. Test Script I benchmark providers by running the same WebSocket client code during market open: import websocket import json def on_message ( ws , message ): data = json .…