Direct Answer

 

Real-time financial data streaming works by establishing a persistent connection between a provider and a client, allowing market updates to be delivered continuously as they occur. Unlike request-based APIs, streaming eliminates the overhead of repeated polling, ensuring that every tick, trade, and quote flows in a high-throughput message stream with minimal delay.

 

Why Streaming Infrastructure Matters

 

In modern trading, the architecture of your data delivery determines your competitive edge.

  • No Polling Overhead: Data is pushed shortly after it is generated without waiting for a client request.
  • Sequential Integrity: Updates arrive in the exact order they occurred at the exchange, which is critical for maintaining an accurate order book.
  • High Throughput: Streaming handles the millions of messages per second that U.S. equities and options can generate without the bottlenecks of standard HTTP headers.

 

Attribute Streaming (NxCore) API Polling (REST)
Connection Persistent (TCP/UDP) Short-lived (HTTP)
Data Delivery Push (near real-time) Pull (on-demand)
Latency Designed for ultra-low latency Milliseconds (200ms+)
Message Logic Every tick included Snapshots or sampled
Overhead Minimal binary headers Heavy HTTP/JSON headers


Comparing Streaming Providers

 

Not all streaming feeds are built equal. While many providers offer “real-time” data, the underlying transport layer varies significantly.

 

Feature NxCore Databento Polygon.io
Architecture Normalized Binary Stream Cloud-Native API / Feed WebSocket / REST
Speed Designed for low-latency environments Variable (cloud delivery may affect latency) Optimized for accessibility and integration
Throughput High-throughput, full-tick feed Usage-based filter Tiered limits

 

 

Frequently Asked Questions

  • What is the difference between TCP and UDP for market data? TCP ensures every packet is delivered in order but can cause “head-of-line blocking” if a packet is lost. UDP is faster but requires the client to handle potential packet loss.
  • Can WebSockets be used for high-frequency trading? WebSockets are generally too slow for HFT due to TCP overhead and may involve server-side batching depending on the provider.
  • Is JSON or Binary better for market data? Binary formats are superior for speed; JSON parsing introduces additional overhead compared to compact binary formats.


Who This Is For (and Who It’s Not)

 

Who This Is For

  • Quant teams building execution systems that require tick-by-tick precision.
  • Infrastructure engineers looking to minimize intermediary processing.
  • Firms requiring high-throughput ingestion for U.S. equities and options.

Who This Is NOT For

  • Retail traders using standard web dashboards for manual trading.
  • Users who only require end-of-day or delayed snapshots.