Amazon Technologies, Inc.

Divyank Duvedi

Chase Kernan

Akshat Vig

Somasundaram Perianayagam

Nicholas Gordon

Conor Patrick Cahill

Ravi Math

Jeffrey John Wierer

Anurag Mishra

Richard Krog

Elie Gharios

Robert Kenny

Uma Ganesh Sadras Sudhakar

Mohammed Noman Mulla

A database management system obtains key ranges associated with partitions of a database table, and determines that restoration of data associated with at least one of these partitions would take time that is estimated to exceed a goal time. The database management system splits a partition into two or more additional partitions, so that the respective estimated restoration times for data associated with the additional partitions is estimated to be less than the goal time. The database management system then causes the database table to be restored according to partitions that comprises the additional partitions.

Database table restoration for data with skewed distribution

A system for database restoration across service regions. The system includes data storage and backup data storage in the first region. The system includes a frontend for the database service configured to receive, from a client, a request to restore a database to the first region from backups stored in another backup data storage in a second region and to receive an authentication token for the request from the client. The system also includes a backup restore manager service for the first region configured to send, to another backup restore manager service implemented in the second region, a credential request for a second region credential authorizing retrieval of the one or more other backups from the second region. The backup restore manager service sends a backup restore request to retrieve the backups from the other backup data storage and loads the backups to restore the database in the first region.

Secured database restoration across service regions

A system receives a request to import data file(s) from a source data store into a target database. The system reserves a first portion of computing resources that host the target database to import the data file(s). The reservation of the first portion of computing resources permits the import throughput rate of the data file(s) through the first portion of computing resources while maintaining a second portion of the computing resources to support client access to the target database at an access throughput rate. The system initiates import of the data file(s) from the source data store to the target database through one or more storage nodes at the import throughput rate according to the first portion of computing resources. The target database is able to receive access requests from one or more clients during the import of the data file(s) to the target database.

Serverless managed bulk import on a global NoSQL database with selective back pressure

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

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Seattle, WA, United States of America

Divyank Duvedi