Abstract: In one embodiment, a data reconciliation engine works with data store nodes included in a distributed data store system to ensure consistency between the data store nodes. In operation, the data reconciliation receives a different data snapshot from each of the data store nodes. In response, the data reconciliation engine generates one or more recommendations designed to resolve inconsistencies between the data snapshots. The data reconciliation engine then transmits each recommendation to a different data store node. Because the data reconciliation engine performs many of the resource-intensive operations included in the data reconciliation process, the resources of the data store nodes may focus primarily on processing client requests instead of performing data reconciliation operations.

Abstract: In various embodiments, a node manager configures a “new” node as a replacement for an “unavailable” node that was previously included in a distributed data store. First, the node manager identifies a source node that stores client data that was also stored in the unavailable node. Subsequently, the node manager configures the new node to operate as a slave of the source node and streams the client data from the source node to the new node. Finally, the node manager configures the new node to operate as one of multiple masters nodes in the distributed data store. Advantageously, by configuring the node to implement a hybrid of a master-slave replication scheme and a master-master replication scheme, the node manager enables the distributed data store to process client requests without interruption while automatically restoring the previous level of redundancy provided by the distributed data store.

Abstract: In various embodiments, a node manager configures a “new” node as a replacement for an “unavailable” node that was previously included in a distributed data store. First, the node manager identifies a source node that stores client data that was also stored in the unavailable node. Subsequently, the node manager configures the new node to operate as a slave of the source node and streams the client data from the source node to the new node. Finally, the node manager configures the new node to operate as one of multiple masters nodes in the distributed data store. Advantageously, by configuring the node to implement a hybrid of a master-slave replication scheme and a master-master replication scheme, the node manager enables the distributed data store to process client requests without interruption while automatically restoring the previous level of redundancy provided by the distributed data store.

Abstract: In one embodiment, a data reconciliation engine works with data store nodes included in a distributed data store system to ensure consistency between the data store nodes. In operation, the data reconciliation receives a different data snapshot from each of the data store nodes. In response, the data reconciliation engine generates one or more recommendations designed to resolve inconsistencies between the data snapshots. The data reconciliation engine then transmits each recommendation to a different data store node. Because the data reconciliation engine performs many of the resource-intensive operations included in the data reconciliation process, the resources of the data store nodes may focus primarily on processing client requests instead of performing data reconciliation operations.

Abstract: A technique for providing an API from a server to one of more endpoint devices including receiving a request for data from a endpoint device, retrieving one or more data resources from the data resources available within the server, based upon the request, manipulating the data within the retrieved data resources into a response optimized for the endpoint device, and transmitting the response to the endpoint device.

Abstract: A technique for providing an API from a server to one of more endpoint devices including receiving a request for data from a endpoint device, retrieving one or more data resources from the data resources available within the server, based upon the request, manipulating the data within the retrieved data resources into a response optimized for the endpoint device, and transmitting the response to the endpoint device.