Data processed and made available immediately as it is generated, with minimal delay.
Real-time data systems capture, process, and deliver data within seconds or milliseconds of an event occurring. This is essential for applications where decisions depend on the most current information — traffic management, emergency dispatch, financial trading, or live transit tracking.
Example: A city's open data portal publishes a real-time feed of bus locations. Every 30 seconds, GPS coordinates from each bus are transmitted, processed, and made available through an API. Transit apps use this feed to show live bus positions on a map.
Real-time data requires more infrastructure than batch processing and is only justified when timeliness genuinely matters. Many datasets that appear "live" are actually refreshed on a short batch schedule rather than being truly real-time.