Amazon Technologies, Inc.

Ravi Math

Nicholas Gordon

Akshat Vig

Somasundaram Perianayagam

Sharatkumar Nagesh Kuppahally

James Christopher Sorenson

Vaibhav Jain

Chase Kernan

Sroaj Sosothikul

Avinash Kodakandla

Mazen Moez Ali

Sharan Rajesh Munyal

Wei Xiao

Amit Gupta

Adam Douglas Morley

Rajaprabhu Thiruchi Loganathan

Peter Zhivkov

Remi Paucher

Stefano Stefani

Tate Andrew Certain

Alexander Richard Keyes

Ming-Chuan Wu

Jeffrey John Wierer

Amit Purohit

Lokendra Singh Panwar

Divyank Duvedi

Anshul Gupta

Joseph Robert Idziorek

Sangeeth Prem

Shahzeb Farrukh

Elie Gharios

Robert Kenny

Krishnan Seshadrinathan

Christopher John Anderson

Queries may be made against a non-relational database without impacting the capacities of the non-relational database by enabling performance of queries to a non-relational database via an external query management, backup management, and a non-relational database backup hosted in an external data storage. Query units may be provided to an external query engine to provide parallel units of work for accessing and performing queries on a backup of a database.

Providing query units to support external analytics queries to a backup of a database

Queries may be made against a non-relational database without impacting the capacities of the non-relational database by enabling performance of queries to a non-relational database via an external query management, backup management, and a non-relational database backup hosted in an external data storage. The query management and backup management of the non-relational database service may split transactional load to the non-relational database and analytical load, and furthermore allow selection of a desired data freshness for queries including various time ranges, such as seconds, minutes, or days.

Analytic query processing using a backup of a database

Consistent queries to replicated data may be performed according to global clock values. Time values for updates performed at a data set may be identified according to a global clock. The updates may be replicated to a replicated portion of a data set. Queries directed to the replicated portion of the data set may be performed in response to determining that the time values for updates indicate that the replicated portion of the data set is consistent with a time value identified for the query according to the global clock.

Global clock values for consistent queries to replicated data

A distributed database encrypts tables using table encryption keys protected by a client master encryption key. The client may revoke and subsequently restore authorization to access the client master encryption key. A sweeper process of the distributed database examines encrypted tables and identifies changes to the status of a corresponding client master encryption key. A response to an identified change in status is initiated.

Database with client-controlled encryption key

Offline building of a projected data subset may be performed. A request to create a data set that is a projected subset of data from a source data set may be received. A data store separate from the data store storing the source data set may store a copy of the source data set that is used to replicate items to the projected subset of data according to a schema for the projected data subset. Updates made to the source data set may also be replicated to the projected data subset according to the schema. Conflicts between replicated items and replicated updates to the projected data set may be resolved by comparing a version identifier for the replicated update and replicated item to determine what to store in the projected data subset.

Offline index builds for database tables

A distributed database encrypts a table using a table encryption key protected by a client master encryption key. The encrypted table is replicated among a plurality of nodes of the distributed database. The table encryption key is replicated among the plurality of nodes, and is stored on each node in a respective secure memory. In the event of node failure, a copy of the stored key held by another member of the replication group is used to restore a node to operation. The replication group may continue operation in the event of a revocation of authorization to access the client master encryption key.

A distributed database encrypts tables using table encryption keys protected by a client master encryption key. The client may revoke authorization to access the client master encryption key. Subsequent to a revocation of authority to access the client master encryption key, the distributed database generates interim snapshots of the table using the table encryption key. Also subsequent to the revocation, the distributed database generates a backup of the table using a backup encryption key protected by the client master encryption key.

Methods, systems, and computer-readable media for renaming a database table with minimized application downtime are disclosed. A database receives a table rename request for a table having a first table name. Routing metadata comprises a mapping of the first table name to a table identifier and a mapping of the table identifier to one or more partitions. The table rename request indicates a second table name. The database generates updated routing metadata responsive to the table rename request. The updated routing metadata comprises a mapping of the second table name to the table identifier and the mapping of the table identifier to the one or more partitions. The database receives, from a client application, one or more access requests indicating the second table name. The database routes the one or more access requests to the one or more partitions based at least in part on the updated routing metadata.

Renaming a database table with minimized application downtime

Scalable architecture for propagating updates may be implemented for data replicated from a data set. A node may receive updates to items in a data set that have been committed to the data set. The node may determine whether the update should be applied to a replicated portion of the data set. For updates that should be applied, the node may identify another node that hosts the replicated portion of the data set and send a request to the other node to perform a conditional atomic operation to apply the update to the item in the replicated portion of the data set. The condition may compare a version identifier associated with an update and a current version identifier for the item at the other node. If the condition evaluates true, then the update to the item in the replicated portion may be performed.

Scalable architecture for propagating updates to replicated data

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Redmond, WA, United States of America

Ravi Math