Almost every market-data integration ends up using both REST and WebSocket, but teams routinely reach for the wrong one and pay for it in latency, rate limits or complexity. The distinction is simpler than the debate suggests: REST is for data you request, WebSocket is for data that requests you.
REST: pull what you already know you need
A REST call is a question with an answer. It is ideal when you know exactly what you want and can tolerate the round-trip: yesterday’s daily bars, a company’s fundamentals, a backtest’s worth of historical ticks, the constituents of an index. You ask once, you get a bounded response, you move on. Because each call is stateless, REST is trivially cacheable and easy to reason about — and it is the right tool for the overwhelming majority of historical and reference data.
Where REST hurts is when you use it to simulate a live feed. Polling an endpoint every second to "stream" quotes wastes rate limit, adds a full round-trip of latency to every update, and still misses everything that happens between polls. If you find yourself in a tight polling loop, you have outgrown REST.
WebSocket: subscribe once, receive forever
A WebSocket connection is a standing subscription. You authenticate, you declare the channels and symbols you care about, and the server pushes each update the instant it exists. There is no per-message request, so there is no per-message latency tax and no polling overhead. For trades, quotes, order-book updates, streaming news and live sentiment, this is the only transport that keeps up.
The cost is state. A stream is a long-lived connection that can drop, so production clients need reconnect logic, re-subscription on reconnect, and a plan for the gap — usually a REST backfill for whatever you missed while disconnected. That REST-fills-the-gap pattern is exactly why real systems use both.
The rule of thumb
Stream what is live and unpredictable; pull what is historical or reference. On Pig Data the two share one symbology and one schema, so a tick you stream over WebSocket has the same fields as a tick you pull over REST — your research and production code stop diverging, and the transport becomes an implementation detail instead of a rewrite.