Amazon Technologies, Inc.

Dhruv Goel

Andrew Whitaker

Kanishka Chaturvedi

Pravin Mittal

Stefano Stefani

Sudipto Das

Sandeep Bhatia

Ming-Chuan Wu

Lishi Jiang

Maruthi Manohar Reddy Devarenti

VamsiKrishna Chaitanya Manchem

Abhijeet More

Rajesh Iyer

Nitin Ahuja

Pushap Goyal

Tiratat Patana-anake

Hong Yang

Nilanjan Basu

Abhilash Reddy Koppula

A system to manage database queries including storage devices to implement a data store to store database data and computing devices to implement a query engine. The query engine is configured to receive, from a client, a database query and initiate performance of the query at the data store. The query engine is configured to compare a performance time of the query with a performance time threshold. Based on the performance time exceeding the performance time threshold: send a query identifier for the query and a token indicating that the query has not been completed; and receive, from the client, an additional query comprising the token and the query identifier. Based on a determination that the performance time does not exceed the performance time threshold, send a response to the query to the client, the response comprising data requested by the query.

Paginated synchronous database querying

A non-relational database may be emulated using a relational database with a distributed data store. A request to access the non-relational database may be received at a frontend for a relational database engine that emulates an interface for a non-relational database engine. The request may be translated into the format for the relational database engine and performed by the relational database engine. The relational database engine may access data for the non-relational database at storage nodes that store the data in a relational table column of non-relational data type.

Emulating a non-relational database on a relational database with a distributed data store

A database testing system may generate, based on a randomization process, test data for a database. The system may generate a query that, when processed by the database, produces a first result that comprises the row. The system may modify the query based on a randomization process and in view of the semantic properties of the query language associated with the queries. The system may predict the outcome of the modifies query based on the semantic properties and on the generated test data. The system may verify that the modified query, when processed by the database, produces results consistent with the prediction.

Semantic-aware fuzz-based functional testing

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Seattle, WA, United States of America

Dhruv Goel