Abstract: A query is received. The query is executed at a database instance that supports a first database service and a second database service. Based on historical performance data, it is determined that an optimal execution path of the query includes splitting the query across the first database service and the second database service. In response to determining the optimal execution path, the query is split into a first component query in a first query language compatible with the first database service and a second component query in a second query language compatible with the second database service. The first component query is executed at the first database service. The second component query is executed at the second database service.

Abstract: A determination is made whether a received database query is to be processed by either a first database, a second database, or at least in part by both the first and second databases including by determining whether the query meets criteria to split the query for processing across the first and second databases. The first and second databases store shared synchronized records, the first database configured to store the records in a column-oriented format and the second database configured to store the records in a row-oriented format. In response to a determination that the query meets the criteria to split the query, a first and second component query of the database query are generated for the first and second databases, respectively, the second component query based at least in part on a result of the first component query. The execution of the first and second component queries is pipelined.

Abstract: Systems and method for improving query performance by querying an appropriate database engine based on the operation of the query request is provided. In one aspect, this approach involves querying a row-oriented database, querying a column-oriented database, or blacklisting the query request. In particular, updating the column-oriented database involves delete and insert operations. By maintaining updated databases and querying appropriate database engines, the response time of a query request may be improved.

Abstract: Systems and method for improving query performance by querying an appropriate database engine based on the operation of the query request is provided. In one aspect, this approach involves querying a row-oriented database, querying a column-oriented database, or blacklisting the query request. In particular, updating the column-oriented database involves delete and insert operations. By maintaining updated databases and querying appropriate database engines, the response time of a query request may be improved.

Abstract: A determination is made whether a received database query is to be processed by either a first database, a second database, or at least in part by both the first and second databases including by determining whether the query meets criteria to split the query for processing across the first and second databases. The first and second databases store shared synchronized records, the first database configured to store the records in a column-oriented format and the second database configured to store the records in a row-oriented format. In response to a determination that the query meets the criteria to split the query, a first and second component query of the database query are generated for the first and second databases, respectively, the second component query based at least in part on a result of the first component query. The execution of the first and second component queries is pipelined.

Abstract: The present approach relates to improving query performance in a database context. Examples of query improvement are described in the context of certain query patterns, one or more of which may be observed in a given query. When a given query pattern is observed, changes may be made to the query at the application or database level to improve performance of the respective query. Query improvements may be performed in a manner transparent to the user.

Abstract: Systems and method for improving query performance by querying an appropriate database engine based on the operation of the query request is provided. In one aspect, this approach involves querying a row-oriented database, querying a column-oriented database, or blacklisting the query request. In particular, updating the column-oriented database involves delete and insert operations. By maintaining updated databases and querying appropriate database engines, the response time of a query request may be improved.

Abstract: A database server may include a master table schema that defines a database table's configuration and an arrangement for corresponding shadow tables. The shadow tables contain data related to contiguous and non-overlapping time periods and writing to the shadow tables occurs in a rotational fashion so that only one active table is written to at any point. The server may upgrade the master table schema. The server then may determine that a rotation event has occurred where a first shadow table is active and a second shadow table is associated with an oldest of the contiguous and non-overlapping time periods. In response, the server may delete data in the second table, determine that the schema has been upgraded since the second table was most recently active, upgrade the second table's schema to match the schema, and set the second table to active enabling writing to the second table.

Abstract: Systems and method for improving query performance by querying an appropriate database engine based on the operation of the query request is provided. In one aspect, this approach involves querying a row-oriented database, querying a column-oriented database, or blacklisting the query request. In particular, updating the column-oriented database involves delete and insert operations. By maintaining updated databases and querying appropriate database engines, the response time of a query request may be improved.

Abstract: The present approach relates to improving query performance in a database context. Examples of query improvement are described in the context of certain query patterns, one or more of which may be observed in a given query. When a given query pattern is observed, changes may be made to the query at the application or database level to improve performance of the respective query. Query improvements may be performed in a manner transparent to the user.

Abstract: The present approach relates to improving query performance in a database context. Examples of query improvement are described in the context of certain query patterns, one or more of which may be observed in a given query. When a given query pattern is observed, changes may be made to the query at the application or database level to improve performance of the respective query. Query improvements may be performed in a manner transparent to the user.

Abstract: A database server may include a master table schema that defines a database table's configuration and an arrangement for corresponding shadow tables. The shadow tables contain data related to contiguous and non-overlapping time periods and writing to the shadow tables occurs in a rotational fashion so that only one active table is written to at any point. The server may upgrade the master table schema. The server then may determine that a rotation event has occurred where a first shadow table is active and a second shadow table is associated with an oldest of the contiguous and non-overlapping time periods. In response, the server may delete data in the second table, determine that the schema has been upgraded since the second table was most recently active, upgrade the second table's schema to match the schema, and set the second table to active enabling writing to the second table.

Abstract: The present approach relates to improving query performance in a database context. Examples of query improvement are described in the context of certain query patterns, one or more of which may be observed in a given query. When a given query pattern is observed, changes may be made to the query at the application or database level to improve performance of the respective query. Query improvements may be performed in a manner transparent to the user.