Amazon Technologies, Inc.

Edward Paul Murray

Ilia Gilderman

John MacDonald Winford

Nicolas Anton Medhurst Hertl

Chen Zhang

Grant Alexander Macdonald McAlister

Jeremiah Wilton

Michael J Russo

Eran Schitzer

Rostislav Babocichin

Harpreet Kaur Chawla

Arun Kumar Thiagarajan

Danial George Neault

Sameer Malik

Samujjwal Roy

Gal Eliraz Levonai

Venu Reddy

Michael D Soo

Siva Raghupathy

Shireesh Prakash Gupta

Ramya Kaushik

Satheesh Peringandookaran Subramanian

Knievel Co

A workload of a database may be evaluated to provide a database migration recommendation. A request for a recommendation to migrate a database to a new host may be received. An evaluation of the workload of a client application of the database at a current host may be performed. The migration recommendation may be returned based on the evaluation of the workload of the client application of the database. In some embodiments, the migration recommendation may trigger an automated migration of the database to the new host.

Evaluating workload for database migration recommendations

Described herein is technology for replicating data from a source database to one or more target databases at different points in time. The system receives a request to replicate a data set stored in a source database. The system stores a copy of a first subset of the data set from the source database to a target database at a first time. The system stores a copy of a second subset of the data set from the source database to the target database at a second time.

Multi-tiered data replication

A method and system for validating data migrated from a source database to a target database and storing validation metrics resulting from validating the data are described. The system receives validation information to be used to validate data to be migrated from a source database to a target database. The system validates the data using the validation information and stores validation metrics resulting from validating the data.

Data validation of data migrated from a source database to a target database

Validation of a migration task to migrate data from one data store to another may be performed prior to the migration of the data. Parameters associated with the migration may be evaluated according to one or more types of validations for the migration task. In some embodiments, users may specify the validations to perform for the migration task. A determination as to whether the migration task is valid may be performed for the migration task based on the parameter evaluations. A result indicating whether the migration task is valid may be provided to a user.

Migration task validation before data migration

Tables in the database management system may be divided into partitions, and partitions may be further subdivided into subpartitions. Subpartitions may be ordered on time or date values and boundaries between subpartitions may be defined based on various time-based intervals. A subpartition management policy may be defined. Older subpartitions may be automatically deleted, moved to archival storage or moved to a secondary database. Subpartitions may be automatically created and reserved for future use. Preexisting subpartitions may be automatically split and merged into new subpartitions conformant to the subpartition management policy.

Rolling subpartition management

A distributed database management system maintains logical collections of data. The collections may grow at varying rates, and may place storage and workload processing demands on the system that change over time. A value representative of the current maximum of capacity utilization for computing nodes in the system may be calculated. An estimate of the number of days for each computing node to reach the current maximum may be calculated, and compared to an average number of days. Computing nodes whose number of days is above the average may be selected to receive new logical collections of data.

Data growth balancing

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Sammamish, WA, United States of America

Edward Paul Murray