Abstract: A database compression system includes and analyzer, a counting engine, and a mapping engine. The analyzer analyzes a schema of a database by maintaining a list of attributes and corresponding values. The analyzer also analyzes a selection of entries in the database. The counting engine determines a frequency of occurrence of each attribute/value pair in the selection of entries. The mapping engine assigns a condensed code to a character string determined on the basis of the attribute/value pair with a highest frequency of occurrence.

Abstract: Methods and a computing node for cloud bursting a first instance of a database stored in a computing node, to a second instance of the database instantiated in a cloud computing node are described. A request for a data object is received at the second instance, a determination whether a local copy of the requested data object is stored in the second instance is made and, in response to determining that a local copy of the requested data object is not stored in the second instance, a request for the data object is sent from the second instance to the first instance. The second instance receives a copy of the requested data object and stores the copy of the requested data object in the second instance. This enables near-instant cloud bursting of the database without having to wait for the entire contents of the first instance to be migrated to the second instance.

Abstract: A database compression system includes and analyzer, a counting engine, and a mapping engine. The analyzer analyzes a schema of a database by maintaining a list of attributes and corresponding values. The analyzer also analyzes a selection of entries in the database. The counting engine determines a frequency of occurrence of each attribute/value pair in the selection of entries. The mapping engine assigns a condensed code to a character string determined on the basis of the attribute/value pair with a highest frequency of occurrence.