Direct Answer

Modernizing a market data pipeline involves replacing legacy “request-response” models with event-driven, streaming architectures. By utilizing in-memory processing and high-speed binary feeds, firms can ingest millions of messages per second and respond to market movements in real-time.

Feature Legacy Middleware Modern Low-Latency Pipeline
Data Source Aggregated API Polling Low-latency streaming feed
Processing Disk-based / Batching In-Memory / Real-time
Connectivity Remote Cloud Gateways Co-located or low-latency feeds
Latency Milliseconds to Seconds Microseconds (in optimized setups)

 


Frequently Asked Questions

  • Is Kafka good for market data? Kafka can achieve low latency with careful tuning, but for the most time-sensitive tasks, lighter-weight alternatives or custom ring buffers are often preferred.
  • Why move to in-memory processing? Reading and writing to a disk is significantly slower than RAM, making in-memory databases essential for real-time order books.


Who This Is For (and Who It’s Not)

Who This Is For

  • Engineering leads redesigning legacy infrastructure for better performance.
  • Teams scaling their systems to handle increased market volatility and volume.

Who This Is NOT For

  • Firms with low-frequency data needs where latency is not a bottleneck.