Amazon Technologies, Inc.

Aakash Shah

Kamal Kant Gupta

Saileshwar Krishnamurthy

Anurag Windlass Gupta

Alexandre Olegovich Verbitski

Tengiz Kharatishvili

Zhaohui Zhang

Stefano Stefani

Gopi K Attaluri

Yuri L Volobuev

Yongsik Yoon

Murali Brahmadesam

Sangyong Hwang

Xiaofeng Bao

Jeffrey Davis

Debanjan Saha

Shriram Sridharan

Sailesh Krishnamurthy

Hyungsoo Jung

Volodymyr Verovkin

Dhruva Ranjan Chakrabarit

Aleksandr Valerevich Feinberg

Namrata Bapat

Sheng-Liang Song

Change data capture is performed asynchronously for direct transfer to a stream processor. When updates to a database as part of database transactions are performed, a transaction log is generated that describes the database transactions. The transaction log may be evaluated to determine indications of changes included in the database transactions. The indications of the changes may be stored in memory according to the database transactions that include the indications of the changes. When a database transaction is determined to be committed to the database, the change indications may be sent directly from the memory to the stream processor.

Asynchronous change data capture for direct external transmission

Storage level query processing may be implemented for processing database queries. Nodes that can access a database may perform parallel processing for at least a portion of a database query. An indication may be received that specifies parallel processing for the database query. The nodes can then be caused to perform the portion of the query as part of providing a result in response to the database query instead of a node, such as a query engine node, that received the database query.

Storage level parallel query processing

Online reordering for database table columns may allow a user to reorder the columns of a database table without taking the database offline. A mapping between different column orders for a database table may be generated and stored in response to a request to reorder columns in a database table. When a portion of the database table is accessed, the columns of the database table in the accessed portion of the database table may be reordered to perform the access request.

Online reordering of database table columns

A data store may implement on-demand data schema modifications. Request to change a schema for a data set in a data store may be received and a description of the change recorded as part of a schema history for the data set. The request to change the schema may then be acknowledged. When access requests directed to the data set are received at the data store, the schema history for the data set may be evaluated. If the schema history indicates that data that is to be accessed in order to service the data store needs to include one or more changes in the schema history, then a version of the schema that includes the one or more changes may be applied to the data.

On-demand data schema modifications

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Santa Clara, CA, United States of America

Aakash Shah