Amazon Technologies, Inc.

Debanjan Saha

Anurag Windlass Gupta

Saileshwar Krishnamurthy

Alexandre Olegovich Verbitski

Kamal Kant Gupta

Tengiz Kharatishvili

Sandor Loren Maurice

Alexey Kuznetsov

Alok Nandan Nikhil

Lawrence Douglas Webley

Bohan Liu

Yuhui Yuan

Yoni Shalom

Jagdeep Singh Sidhu

Mushahid Alam

Siyuan Xing

Yibo Zhu

Nicholas Piers O'Shea

Hongbo Song

Gopi K Attaluri

Yuri L Volobuev

Murali Brahmadesam

Joseph Andrew Tucek

Jeffrey Davis

Shriram Sridharan

Aakash Shah

Volodymyr Verovkin

Dhruva Ranjan Chakrabarit

Aleksandr Valerevich Feinberg

Namrata Bapat

Proxy-based scaling may be performed for databases. A proxy may be implemented for a database that can establish a connection between the proxy and a database engine to perform a database queries received from a client at the proxy. A scaling event may be detected for the database responsive to which the proxy may establish a connection with a new database engine which may, in some embodiments, have different capabilities or resources that address the features or criteria that triggered the scaling event. Session state may be copied from the database engine to the new database engine so that the new database engine may be able to provide access to the database on behalf of requests received from the client through the proxy.

Proxy-based database scaling

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

A service provider network implements seamless scaling via proxy replay of session state. Upon a trigger, such as a determination to scale a server, a scaled server may be spun up and an identifier of the scaled server provided to a first (existing) server. The first server sends the identification of the second server, and session state information for each of the connections between the first server and the request router, to the request router. For each of the connections, the request router establishes a new connection between the request router and the second (scaled) server, and replays the session state information for the connection to the second server. The request router then routes traffic between each existing client connection (e.g., the same existing client connection which carried traffic delivered to the first server) and the corresponding new connection to the second server.

Seamless scaling via proxy replay of session state

A dynamic proxy may be implemented for a database that can establish a connection between the proxy and a database engine to perform a database queries received from a client at the proxy. The proxy may receive a connection request (and later database queries) through a first network endpoint from a client. The proxy can then determine based on the source of the connection request a second network endpoint through which to access the database (e.g., the endpoint of the database engine). Once the proxy establishes a connection with the database engine through the second network endpoint, the proxy can request the performance of queries at the database engine instead of the client.

Dynamic proxy for databases

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Los Altos, CA, United States of America

Debanjan Saha