Quote from zzt:
If anyone has experience with Complex Event Processing(CEP)/Event Stream Processing(ESP), I would appreciate your input.
My question(s) is/are very general.
With regards to processing speed and scalability,what are the advantages of CEP/ESP engines vs dedicated C++ algorithms which process streaming data?
There is an awful lot of hype around the subject space of CEP/ESP, but very little data in terms of comparing it to dedicated event based algo's which process streaming price data.
For arb applications custon C++ running under a RTOS is optimum.
For more general algo trading the flexibility and ease of use offered by CEP/ESP solutions might offer an advantage. All all depends on how specific the application is.
For example, say i have a dedicated arb model, which subscribes to real time streaming data, builds its own time series arrays, processes the tick events and sends buy/sell/amend/cancel orders. In effect my data query is static, (i.e. same datafeed subscriptions, same algo) so i dont have need for a streaming data query language.
Where is the advantage of a CEP engine? Where would it fit in the data processing chain so that it would give an advantage? Would there be saleability advantages if I were running 15 arb models in parallel?
To my mind, any generic solution that attempts to solve all streaming data issues in one app. must have trade offs in terms of either data processing or speed vs dedicated data processing algorithms?
Thanks in Advance
For arb applications C++ running under an RTOS is better.
For more general algo trading, the flexibility and ease of use of ESP/CEP solutions might offer an advantage.
It really depends on how specific the application is.
