Abstract: A system that implements a data storage service may store data for a database table in multiple replicated partitions on respective storage nodes. In response to a request to back up a table, the service may back up individual partitions of the table to a remote storage system independently and (in some cases) in parallel, and may update (or create) and store metadata about the table and its partitions on storage nodes of the data storage service and/or in the remote storage system. Backing up each partition may include exporting it from the database in which the table is stored, packaging and compressing the exported partition for upload, and uploading the exported, packaged, and compressed partition to the remote storage system. The remote storage system may be a key-value durable storage system in which each backed-up partition is accessible using its partition identifier as the key.

Abstract: A system that implements a data storage service may store data for database tables in multiple replicated partitions on respective storage nodes. In response to a request to back up a table, the service may export individual partitions of the table from the database and package them to be independently uploaded (e.g., in parallel) to a remote storage system (e.g., a key-value durable storage system). Prior to uploading the exported and packaged partitions to the remote storage system, the service may verify that the exported and packaged partitions can be subsequently restored, which may include unpackaging and/or re-inflating the exported and packaged partitions to create additional unpackaged copies of the partitions, re-importing the additional unpackaged copies of the partitions into the database (e.g., as additional replicas), and/or comparing checksums generated for the exported partitions with checksums generated for the additional unpackaged copies of the partitions.

Abstract: A system that implements a data storage service may store data for a database table in multiple replicated partitions on respective storage nodes. In response to a request to back up a table, the service may back up individual partitions of the table to a remote storage system independently and (in some cases) in parallel, and may update (or create) and store metadata about the table and its partitions on storage nodes of the data storage service and/or in the remote storage system. Backing up each partition may include exporting it from the database in which the table is stored, packaging and compressing the exported partition for upload, and uploading the exported, packaged, and compressed partition to the remote storage system. The remote storage system may be a key-value durable storage system in which each backed-up partition is accessible using its partition identifier as the key.

Abstract: A system that implements a data storage service may store data for database tables in multiple replicated partitions on respective storage nodes. In response to a request to back up a table, the service may export individual partitions of the table from the database and package them to be independently uploaded (e.g., in parallel) to a remote storage system (e.g., a key-value durable storage system). Prior to uploading the exported and packaged partitions to the remote storage system, the service may verify that the exported and packaged partitions can be subsequently restored, which may include unpackaging and/or re-inflating the exported and packaged partitions to create additional unpackaged copies of the partitions, re-importing the additional unpackaged copies of the partitions into the database (e.g., as additional replicas), and/or comparing checksums generated for the exported partitions with checksums generated for the additional unpackaged copies of the partitions.

Abstract: Information describing changes to a collection of items maintained by a database may be stored in a log file. The information in the log file may be converted into a stream of records describing the changes. The records may be directed to a computing node selected for performing a trigger function in response to the change, based on applying a hash function to a portion of the record, identifying a hash space associated with a value output by the hash function, and mapping from the hash space to the selected computing node.

Abstract: A cache or other cluster is configuration-aware such that initialization and changes to the underlying structure of the cluster can be dynamically updated for use by a client. A client may use a client driver as an intermediary that is responsible for managing the communication with the cluster. For example, a client driver may resolve an alias from a static configuration endpoint to a storage node. The client driver may request an initial configuration from the storage node and then update configuration from one or more storage nodes that store current configuration of the cluster.

Abstract: A cache or other cluster is configuration-aware such that initialization and changes to the underlying structure of the cluster can be dynamically updated. For example, a client may resolve an alias from a static configuration endpoint to a node in a cluster. The client may request initial configuration from the node and then update configuration from nodes that store the current configuration of the cluster.

Abstract: A cache cluster is configuration-aware such that client initialization, access to replicated cached data and changes to the underlying structure of the cache cluster can be dynamically updated. For example, a management system monitoring a cache cluster notices a large number of requests for a key that causes a significant load on a first memory caching node. To reduce the load on the first memory caching node, the management system may cause cached data related to the key to be replicated to a second memory caching node. A configuration stored in one or more of the memory caching nodes may be updated by the management system to allow both memory caching nodes to serve the requests for the key to clients.