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Pipelining Vector-Based Statistical Functions in SQL for Low Latency

Database management systems (DBMSs) can greatly accelerate processing of time series data (such as market data) via a column-based approach. McObject’s eXtremeDB Financial Edition database enables column-based handling via its ‘sequence’ data type, and its library of vector-based statistical functions. This video presents the technique of pipelining these functions in SQL to improve performance by maximizing the proportion of relevant market data that is loaded into the CPU cache and reducing data transfers between CPU cache and main memory.


Introducing eXtremeDB Financial Edition

Financial systems today manage increasing volumes of market data, in applications such as algorithmic trading, risk management and order matching. McObject’s eXtremeDB Financial Edition is an in-memory database system designed to break through the data management bottleneck in capital markets IT. This video provides an overview and some background on McObject.

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