Abstract: Windowed queries with event-based open times are described for use in data analytics for streaming data. A window semantic may be used to define windowed queries of an analytics application that, when executed against an incoming data stream, open a window at a time when a first event associated with a grouping key is received by a windowed query. The window remains open for a predefined duration specified in the windowed query, and query results may be generated based on any events associated with the grouping key that are received while the window remains open. After a lapse of the predefined duration, the window closes, and the query results may be output in association with the window.

Abstract: To achieve long running batch updates, a transaction aggregator layer and one or more data aggregation queues, such as a command queue, are placed between one or more clients and a database. Writes go to the database aggregator layer and are enqueued in the appropriate data aggregation queue, which may be allocated by transaction. Committing the transaction drains the queue and writes the contents of the queue in one transaction-like update to the database. By using the transaction logic in the transaction aggregator layer, transaction-like behavior may be achieved that allows both updates and transactions to scale with less impact on database servers.