Google Inc.

Justin Levandoski

Yuri L Volobuev

Anoop Kochummen Johnson

Thibaud Baptiste Hottelier

Bigang Li

Shuang Guan

Deepak Choudhary Nettem

Victor Sergeyevich Agababov

Aspects of the disclosure are directed to merging data lake openness with scalable metadata for managed tables in a cloud database platform, allowing for atomicity, consistency, isolation, and durability (ACID) transactions, performant data manipulation language (DML), higher throughput stream ingestion, data consistency, schema evolution, time travel, clustering, fine-grained security, and/or automatic storage optimization. Table data is stored in various open-source file formats in cloud storage while physical metadata of the table data is stored in a scalable metadata storage system.

Managed tables for data lakes

Aspects of the disclosure are directed to a metadata cache for extending data warehouse features to data lakes. The metadata cache can accelerate query execution by directly accessing unmanaged data from the data lake rather than accessing the data through the data warehouse. The metadata cache can allow for filtering the unmanaged data to improve the speed of retrieving data for executing a query.

Query acceleration and metadata caching

Growing community of inventors

Seattle, WA, United States of America

Justin Levandoski