Abstract: The disclosure is directed to storing data in different tiers of a database based on the access pattern of the data. Immutable data, e.g., data that does not change or changes less often than a specified threshold, is stored in a first storage tier of the database, and mutable data, e.g., data that changes more often than immutable data, is stored in a second storage tier of the database. The second storage tier of the database is more performant than the first storage tier, e.g., the second storage tier has a higher write endurance and a lower write latency than the first storage tier. All writes to the database are performed at the second storage tier and reads on both storage tiers. The storage tiers are synchronized, e.g., the set of data is copied from the second to the first storage tier based on a trigger, e.g., a specified schedule.

Abstract: The disclosure is directed to storing data in different tiers of a database based on the access pattern of the data. Immutable data, e.g., data that does not change or changes less often than a specified threshold, is stored in a first storage tier of the database, and mutable data, e.g., data that changes more often than immutable data, is stored in a second storage tier of the database. The second storage tier of the database is more performant than the first storage tier, e.g., the second storage tier has a higher write endurance and a lower write latency than the first storage tier. All writes to the database are performed at the second storage tier and reads on both storage tiers. The storage tiers are synchronized, e.g., the set of data is copied from the second to the first storage tier based on a trigger, e.g., a specified schedule.

Abstract: Techniques are provided for (1) extending SQL to support direct invocation of frequent itemset operations, (2) improving the performance of frequent itemset operations by clustering itemset combinations to more efficiently use previously produced results, and (3) making on-the-fly selection of the occurrence counting technique to use during each phase of a multiple phase frequent itemset operation. When directly invoked in an SQL statement, a frequent itemset operation may receive input from results of operations specified in the SQL statement, and provide its results directly to other operations specified in the SQL statement. By clustering itemset combinations, resources may be used more efficiently by retaining intermediate information as long as it is useful, and then discarding it to free up volatile memory.