Amazon Technologies, Inc.

Matthew William Berry

Alazel Acheson

Srikanth Mandadi

Chris Baker

Marvin Michael Theimer

Khaled Salah Sedky

Mahendra Manshi Chheda

Anders Samuelsson

Slavka Praus

Christopher Ryan Baker

Ankit Kumar

Ankul Rastogi

Amit Sahasrabudhe

Rajesh Khetan

Shivam Gujral

A distributed data store may maintain versioned hierarchical data structures. Different versions of a hierarchical data structure may be maintained consistent with a transaction log for the hierarchical data structure. When access requests directed to the hierarchical data structure are received, a version of the hierarchical data structure may be identified for processing an access request. For access requests with snapshot isolation, the identified version alone may be sufficient to consistently process the access request. For access requests with higher isolation requirements, such as serializable isolation, transactions based on the access request may be submitted to the transaction log so that access requests resulting in committed transactions may be allowed, whereas access requests resulting in conflicting transactions may be denied.

Versioned hierarchical data structures in a distributed data store

Service interruptions in a multi-tenancy, network-based storage system can be mitigated by constraining the execution of queries. In various examples, a network-based storage system may receive a request to execute a query against data maintained by the network-based storage system. The network-based storage system may perform a unit of work to execute the query, progressing through some, but not all, of a set of operations that are to be completed for completing execution of the query. Upon completion of the unit of work, query execution may be paused, query state data may be saved, and query results may be generated for consumption by the requesting computing device. In some embodiments, tokens that are usable to resume query execution based on the saved query state data may be sent to customer computing devices for resuming query execution on-demand.

Constrained query execution

Techniques for implementing conflict-free replicated data types in a database are described. A first database replica of a database hosted by a provider network receives an identifier of a first operation to perform on an element stored in the database, the element being of a conflict-free replicated data type. A second database replica of the database receives an identifier of a second operation to perform on the element. The second operation is determined to not conflict with the first operation. The first operation and the second operation are performed on the element stored by the first database replica. The first operation and the second operation are performed on the element stored by the second database replica.

Conflict-free replicated data types in a database

Scaling events may be detected for hosting hierarchical data structures. Scaling events may be detected to modify the capacity of a data store for hierarchical data structures to handle changing write workloads, read workloads, or storage capacity. Hierarchical data structures may be moved from one group of storage hosts to another group of storage hosts according to a filtered snapshot that includes the hierarchical data structures to be moved that is provided to the destination storage hosts. Changes made to the hierarchical data structures made at the source storage hosts during the move can be applied to the filtered snapshot so that the hierarchical data structures may be made available at the destination storage hosts inclusive of the changes.

Scaling events for hosting hierarchical data structures

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Matthew William Berry