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The term "near real-time" or "nearly real-time" (NRT), in telecommunications and computing, refers to the time delay introduced, by automated data processing or network transmission, between the occurrence of an event and the use of the processed data, such as for display or feedback and control purposes. For example, a near-real-time display ...
Therefore, another system is needed. Real-time databases may be modified to improve accuracy and efficiency and to avoid conflict, by providing deadlines and wait periods to insure temporal consistency. Real-time database systems offer a way of monitoring a physical system and representing it in data streams to a database. A data stream, like ...
Such data is usually processed using real-time computing although it can also be stored for later or off-line data analysis. Real-time data is not the same as dynamic data. Real-time data can be dynamic (e.g. a variable indicating current location) or static (e.g. a fresh log entry indicating location at a specific time).
Time series data provides a historical context to the analysis typically associated with complex event processing. This can apply to any vertical industry such as finance [14] and cooperatively with other technologies such as BPM. The ideal case for CEP analysis is to view historical time series and real-time streaming data as a single time ...
A real-time operating system (RTOS) is an operating system (OS) for real-time computing applications that processes data and events that have critically defined time constraints. An RTOS is distinct from a time-sharing operating system, such as Unix , which manages the sharing of system resources with a scheduler, data buffers, or fixed task ...
An OLTP system is an accessible data processing system in today's enterprises. Some examples of OLTP systems include order entry, retail sales, and financial transaction systems. [5] Online transaction processing systems increasingly require support for transactions that span a network and may include more than one company.
Such event-driven processing is a basic tenet of real-time business intelligence. In this context, "real-time" means a range from milliseconds to a few seconds (5s) after the business event has occurred. While traditional BI presents historical data for manual analysis, RTBI compares current business events with historical patterns to detect ...
Nevertheless, the overall idea is to make selected real-time event data available to queries with very low latency, while the entire data set is also processed via a batch pipeline. The latter is intended for applications that are less sensitive to latency and require a map-reduce type of processing.