Alex Pinkin describes the difference a column store, Infobright, made to solving their problems implementing dashboards, reports, and alerts:
What is the secret sauce in Infobright? First, its column oriented storage model which leads to smaller disk I/O. Second, its “knowledge grid” which is aggregate data Infobright calculates during data loading. Data is stored in 65K Data Packs. Data Pack nodes in the knowledge grid contain a set of statistics about the data that is stored in each of the Data Packs. For instance, Infobright can pre-calculate min, max, and avg value for each column in the pack during the load, as well as keep track of distinct values for columns with low cardinality. Such metadata can really help when executing a query since it’s possible to ignore data packs which have no data matching filter criteria. If a data pack can be ignored, there is no penalty associated with decompressing the data pack.
Compared to our MySQL implementation, Infobright eliminated the need to create and manage indexes, as well as to partition tables.
Original title and link: An Infobright Column Store Use Case ( ©myNoSQL)