Smart Infrastructure & Smart Applications for the Smart Business – Infrastructure & Application Performance Monitoring
Data Warehouse Automation & Real-time Data – Reducing Time to Value in a Distributed Analytical Environment
As we head down the road towards real-time event-driven computing and move gradually away from batch processing it is clear that the number of events in some vertical industries is going to be enormous. Not surprising therefore that if we are looking to analyse this data before it reaches a data warehouse then in-memory data is going to be essential to scale up complex event processing (CEP) and business activity monitoring (BAM). You could argue that as solid state disk starts to replace spinning disks that it will all be in memory in the not too distant future. In my opinion we are going to start to see parallel query processing and scoring happening in parallel on in memory data. A good example of this is the strategic partnership emerging between Teradata and SAS which offers deployment of scoring models developed in SAS in the Teradata DBMS. This kind of functionality is the beginnings of massively parallel scoring on in memory data. Also other database vendors such as IBM and Oracle are investing in in-memory extensions to their database products.
If you are looking at scaling CEP or BAM on large volumes of events then it would seem that in-support for handling memory data is going to be high on your shopping list