Abstract: Managing databases implemented in a cloud computing environment. A method includes detecting that a database implemented in the cloud computing environment is in a state of non-use. The method further includes as a result of detecting that a database implemented in the cloud computing environment is in a state of non-use, instantiating a workload in the cloud computing environment to deactivate the database. The workload is configured to store metadata for the database and database data remotely in cloud storage such that the database can be reactivated at a later time.

Abstract: Application service configuration of a timeframe for performing dataloss failover (failover that does not attempt full data replication to the secondary data store) from a primary data store to the secondary data store. A data-tier service, such as perhaps a database as a service (or DBaaS), could receive that configuration from the application service and automatically perform the dataloss failover as configured by the application service. This relieves the application service from having to manage the failover workflow while still allowing the application service to appropriately balance the timing of dataloss failover, which will depend on a very application-specific optimal balance between the negative effects of operational latency versus dataloss.

Abstract: Techniques for allowing access to shared cloud resource using private network addresses are disclosed herein. In one embodiment, a connection packet representing a connection request to a shared cloud resource in the cloud computing system can be intercepted. In response, the connection packet can be encapsulated with data representing one or more of a VNET ID, a VNET source address, or a VNET destination address of a virtual network from which the connection packet is received. The encapsulated connection packet can then be forwarded to the shared cloud resource while retaining the data representing one or more of the VNET ID, the VNET source address, or the VNET destination address for access control at the shared cloud resource.

Abstract: A maximum lag between data stores can be specified that corresponds to a recovery point objective defined in a service level agreement. Lag can be monitored during a data replication between a primary data store and a secondary data store located in geographically different regions. Activity on the primary data store including incoming data transactions can be throttled as a function of the lag and the maximum lag.

Abstract: Techniques for allowing access to shared cloud resource using private network addresses are disclosed herein. In one embodiment, a connection packet representing a connection request to a shared cloud resource in the cloud computing system can be intercepted. In response, the connection packet can be encapsulated with data representing one or more of a VNET ID, a VNET source address, or a VNET destination address of a virtual network from which the connection packet is received. The encapsulated connection packet can then be forwarded to the shared cloud resource while retaining the data representing one or more of the VNET ID, the VNET source address, or the VNET destination address for access control at the shared cloud resource.

Abstract: Application service configuration of a timeframe for performing dataloss failover (failover that does not attempt full data replication to the secondary data store) from a primary data store to the secondary data store. A data-tier service, such as perhaps a database as a service (or DBaaS), could receive that configuration from the application service and automatically perform the dataloss failover as configured by the application service. This relieves the application service from having to manage the failover workflow while still allowing the application service to appropriately balance the timing of dataloss failover, which will depend on a very application-specific optimal balance between the negative effects of operational latency versus dataloss.

Abstract: Application service configuration of a timeframe for performing dataloss failover (failover that does not attempt full data replication to the secondary data store) from a primary data store to the secondary data store. A data-tier service, such as perhaps a database as a service (or DBaaS), could receive that configuration from the application service and automatically perform the dataloss failover as configured by the application service. This relieves the application service from having to manage the failover workflow while still allowing the application service to appropriately balance the timing of dataloss failover, which will depend on a very application-specific optimal balance between the negative effects of operational latency versus dataloss.

Abstract: Application service configuration of a timeframe for performing dataloss failover (failover that does not attempt full data replication to the secondary data store) from a primary data store to the secondary data store. A data-tier service, such as perhaps a database as a service (or DBaaS), could receive that configuration from the application service and automatically perform the any dataloss failover as configured by the application service. This relieves the application service from having to manage the failover workflow while still allowing the application service to appropriately balance the timing of dataloss failover, which will depend on a very application-specific optimal balance between the negative effects of operational latency versus dataloss.

Abstract: Architecture that provides the capability to automatically (e.g., dynamically) reorganize (repartition) an existing partition by dividing (splitting) or recombining (merging) logical databases. This reorganization can be performed to logical databases belonging to the same customer, and based on the partitioning of the tables in these databases. This can include not only splitting secondary replicas of a partition or merging secondary replicas of the partition, but also splitting off secondary replicas of the partition to create a new partition and merging two partitions into one partition. Moreover, these operations can occur while the logical databases are accepting workload (online).

Abstract: A maximum lag between data stores can be specified that corresponds to a recovery point objective defined in a service level agreement. Lag can be monitored during a data replication between a primary data store and a secondary data store located in geographically different regions. Activity on the primary data store including incoming data transactions can be throttled as a function of the lad and the maximum lag.

Abstract: Managing databases implemented in a cloud computing environment. A method includes detecting that a database implemented in the cloud computing environment is in a state of non-use. The method further includes as a result of detecting that a database implemented in the cloud computing environment is in a state of non-use, instantiating a workload in the cloud computing environment to deactivate the database. The workload is configured to store metadata for the database and database data remotely in cloud storage such that the database can be reactivated at a later time.

Abstract: A maximum lag between data stores can be specified that corresponds to a recovery point objective defined in a service level agreement. Lag can be monitored during a data replication between a primary data store and a secondary data store located in geographically different regions. Activity on the primary data store including incoming data transactions can be throttled as a function of the lag and the maximum lag.

Abstract: Streaming database replication is provided by merging a stream of user transactions with a stream of copy transactions comprising copy data into a combined stream on a source. A target receives a single stream that includes copy transaction and concurrent user transactions in an order that enables conflicts between data being copied and user transactions to be handled correctly. Furthermore, locks applied to data subject to a copy transaction or user transaction can be released once the copy transaction or user transaction is added to the combined stream.

Abstract: Methods, systems, and computer program products are provided for partitioning online databases. Online database operations, such as, for example, SPLIT, MERGE, and DROP, are used to alter the arrangement of partitions in a federated database. A SPLIT operation splits rows at one partition across a plurality of other partitions. A MERGE operation merges rows at a plurality of partitions in to one partition. A DROP operation shifts responsibility for rows of data from one partition to another partition and then drops the rows from the one partition.

Abstract: A database associated with a primary database cluster may be replicated in a backup database cluster located in a different location in order to provide a highly-available fault tolerant database service. The databases are reconciled through a cluster management module distributed in each database cluster. The cluster management module uses a set of reconciliation data structures to track locally the reconciled states of each database in each database cluster, the operations made locally to the databases in each database cluster, and the author of the operations. The cluster management module in each database cluster engages in a stateless messaging protocol using the set of reconciliation data structures to determine whether or not the databases may be reconciled.

Abstract: Methods, systems, and computer program products are provided for partitioning online databases. Online database operations, such as, for example, SPLIT, MERGE, and DROP, are used to alter the arrangement of partitions in a federated database. A SPLIT operation splits rows at one partition across a plurality of other partitions. A MERGE operation merges rows at a plurality of partitions in to one partition. A DROP operation shifts responsibility for rows of data from one partition to another partition and then drops the rows from the one partition.

Abstract: Architecture that provides the capability to automatically (e.g., dynamically) reorganize (repartition) an existing partition by dividing (splitting) or recombining (merging) logical databases. This reorganization can be performed to logical databases belonging to the same customer, and based on the partitioning of the tables in these databases. This can include not only splitting secondary replicas of a partition or merging secondary replicas of the partition, but also splitting off secondary replicas of the partition to create a new partition and merging two partitions into one partition. Moreover, these operations can occur while the logical databases are accepting workload (online).

Abstract: Architecture that provides the capability to automatically (e.g., dynamically) reorganize (repartition) an existing partition by dividing (splitting) or recombining (merging) logical databases. This reorganization can be performed to logical databases belonging to the same customer, and based on the partitioning of the tables in these databases. This can include not only splitting secondary replicas of a partition or merging secondary replicas of the partition, but also splitting off secondary replicas of the partition to create a new partition and merging two partitions into one partition. Moreover, these operations can occur while the logical databases are accepting workload (online).

Abstract: Methods, systems, and computer program products are provided for partitioning online databases. Online database operations, such as, for example, SPLIT, MERGE, and DROP, are used to alter the arrangement of partitions in a federated database. A SPLIT operation splits rows at one partition across a plurality of other partitions. A MERGE operation merges rows at a plurality of partitions in to one partition. A DROP operation shifts responsibility for rows of data from one partition to another partition and then drops the rows from the one partition.

Abstract: A database associated with a primary database cluster may be replicated in a backup database cluster located in a different location in order to provide a highly-available fault tolerant database service. The databases are reconciled through a cluster management module distributed in each database cluster. The cluster management module uses a set of reconciliation data structures to track locally the reconciled states of each database in each database cluster, the operations made locally to the databases in each database cluster, and the author of the operations. The cluster management module in each database cluster engages in a stateless messaging protocol using the set of reconciliation data structures to determine whether or not the databases may be reconciled.