Snowflake Inc.

Oracle International Corporation

Snowflake Computing Inc.

Snowflake Lnc.

Benoit Dageville

Thierry Cruanes

Marcin Zukowski

Subramanian Muralidhar

Istvan Cseri

Allison Waingold Lee

Pui Kei Johnston Chu

Torsten Walther Grabs

Martin Hentschel

Prasanna V Krishnan

Justin Langseth

Matthew J Glickman

Christian Kleinerman

Ashish Motivala

Peter Povinec

Philipp Thomas Unterbrunner

Damien Carru

Shreyas Narendra Desai

Karl Dias

Jiaqi Yan

Mohamed Zait

Khaled Yagoub

Johan Harjono

Kunal Prafulla Nabar

Nileema Shingte

Steven James Pelley

Mark Charles Ramacher

Saurin Shah

Eric Robinson

Gary C Ngai

Florian Andreas Funke

Unmesh Jagtap

William H Waddington

Simon Holm Jensen

Bowen Zhang

Di Wu

Mohamed Ziauddin

Peter Clayton Belknap

Ismail Oukid

Prasanna Rajaperumal

Stefan Richter

Yair Sarig

Marcus Fallen

Igor Demura

Yi Fang

Bhaskar Ghosh

Vishnu Dutt Paladugu

Yizhi Zhu

Jonathan D Klein

Nithin Mahesh

Ganeshan Ramachandran Iyer

Dinesh Das

Varun Ganesh

Spyridon Triantafyllis

Haowei Yu

German Alberto Gil Echeverri

Jiaxing Liang

Graham Wood

Leng Leng Tan

Uri Shaft

Tyler Arthur Akidau

Alex Tsukerman

Sahaj Saini

Abdul Q Munir

Leonidas Galanis

Chieh-Sheng Wang

Tyler Jones

Dinesh Chandrakant Kulkarni

Zheng Mi

Venkateshwaran Venkataramani

Jun Luo

Hong Su

Tirthankar Lahiri

Wei Ey Li

Abhinav Gupta

David Schultz

Polita Paulus

Srikanth Bellamkonda

Ashish Thusoo

Ari Wolfe Mozes

Jae Young Yoon

Gianfranco Putzolu

Sunil Parrokkaren Chakkappen

Vadim Antonov

John Mark Beresniewicz

Amit Ganesh

Carol L Colrain

Hakan Jakobsson

Shrikanth Shankar

Sanjay Kaluskar

Vasudha Krishnaswamy

Sujatha Muthulingam

Ekrem Soylemez

Shilpa Lawande

James G Pan

Kiran Badrinarain Goyal

Andre Kruglikov

Stephen John Vivian

Chao Liang

Example resource management systems and methods are described. In one implementation, a resource manager is to be coupled to one or more virtual data warehouse instances that each comprise a plurality of computing resources. A resource manager receives a query directed to database data. The resource manager determines a task associated with the query. The resource manager distributes the task to a first virtual data warehouse instance of the plurality of virtual data warehouse instances. The resource manager determines that the first virtual data warehouse instance of the plurality of virtual data warehouse instances no longer accesses the database data. The resource manager reconfigures the first virtual data warehouse instance to delete a communication between the first virtual data warehouse instance and the database.

Resource management systems and methods

Systems of methods of directing requests to databases based on client account association is disclosed. A method includes determining a first client account associated with a first request to perform a first transaction. The method includes determining a second client account associated with a second request to perform a second transaction. The method includes selecting, for the first request, a primary deployment that stores a first dataset responsive to determining the first client account associated with the first request. The method includes selecting, for the second request, a secondary deployment that stores a second dataset that includes the first dataset responsive to determining the second client account associated with the second request. The method includes executing, while the primary deployment and the secondary deployment are both available, the first transaction on the first dataset at the primary deployment and the second transaction on the second dataset at the secondary deployment.

Directing requests to databases based on client account association

Embodiments of the present disclosure relate to sharing data using database roles. Database roles are generated within a database container of a provider account. Grants to a particular subset of the plurality of data objects of the database container may be assigned to each of the database roles, and each of the database roles are granted to a share object. The share object is mounted within a consumer account to generate an imported copy of each of the database roles. The imported copy of one or more of the database roles is granted to each of one or more account level roles of the consumer account. When a new object is added to a particular database role, it is immediately available for consumption by any account level roles to which the imported copy of the particular database role has been granted.

Fine-grained access control via database roles

Systems and methods for managing membership in a private data exchange are provided herein. In one embodiment, the method includes creating, in a first data exchange belonging to a first data provider, a first listing. The method further comprises creating, in a second data exchange belonging to a second data provider, a second listing, the second listing comprising a tunnel to the first listing. The method also includes generating, in the second data exchange, a third listing, the third listing comprising data from the second listing and additional data from the second data provider.

Managing version sharing in a data exchange

Replication and failover of data is disclosed. A method includes replicating the data stored in a primary deployment such that the data is further stored in a secondary deployment. The method includes executing one or more transactions on the data at the primary deployment to cause a change to the data to be stored in the primary deployment. The method includes propagating the one or more transactions on the data to the secondary deployment to perform a failover to the secondary deployment while the change to the data is absent from the secondary deployment.

Data replication and data failover in data storage systems

As described herein, a N-Gram index may be created and the search may be conducted using the index, which will lead to faster search results. The N-Gram index may also include partial N-Gram components to capture more relevant data. Moreover, as described herein, the search may also take into account recent log data that has not yet been indexed. Techniques for building an index store using log data and efficiently searching the index store and log data to process search requests are described herein.

Metadata search via N-gram index

A data platform for managing an application as a first-class database object. The data platform includes at least one processor and a memory storing instructions that cause the at least one processor to perform operations including detecting a data request from a browser for a data object located on the data platform, executing a stored procedure, the stored procedure containing instructions that cause the at least one processor to perform additional operations including instantiating a User Defined Function (UDF) server, an application engine, and the application within a security context of the data platform based on a security policy determined by an owner of the data object. The data platform then communicates with the browser using the application engine as a proxy server.

First class database object server application

An anti-abuse system is provided for a data-platform. An anti-abuse scanner of the data-platform detects a creation of an application package by a provider of content to the data platform where the application package includes a set of files for deployment on the data platform. The anti-abuse scanner performs a review o the set of files to detect malicious content where the review is based on a set of analysis rules and generates a deployment decision for the application package based on a result of the review.

Application trust framework

Systems, methods, and devices for batch ingestion of data into a table of a database. A method includes determining a notification indicating a presence of a user file received from a client account to be ingested into a database. The method includes identifying data in the user file and identifying a target table of the database to receive the data in the user file. The method includes generating an ingest task indicating the data and the target table. The method includes assigning the ingest task to an execution node of an execution platform, wherein the execution platform comprises a plurality of execution nodes operating independent of a plurality of shared storage devices collectively storing database data. The method includes registering metadata concerning the target table in a metadata store after the data has been fully committed to the target table by the execution node.

Batch data ingestion in database systems

Techniques for continuous ingestion of files using custom file formats are described. A custom file format may include formats not natively supported by a data system. Unstructured files (e.g., images) may also be considered custom file formats. A custom file format may be set using a user defined table function and scanner options.

Continuous ingestion of custom file formats

Sharing data in a data exchange across multiple cloud computing platforms and/or cloud computing platform regions is described. An example computer-implemented method can include creating a listing in a data exchange, the listing including a data set hosted by a first cloud computing entity. The data set can be shared with a second cloud computing entity. The method further includes receiving a request associated with a customer account of the second cloud computing entity to access the data set of the listing hosted by the first cloud computing entity and replicating at least a subset of the data set of the listing from the first cloud computing entity to a provider account at the second cloud computing entity to be accessible by the customer account at the second cloud computing entity.

Creating a global data sharing listing

Techniques for database replication include a method performed by at least one hardware processor of a resource management node. The method includes detecting a request that a database instance of a database stored at a first network deployment is available at a second network deployment. Responsive to the request, the second network deployment is provisioned with a plurality of data objects. A first data object of the plurality of data objects includes a database shell. The database shell is reconfigured as the database instance of the database based on pushing data of the database into the database shell. Access to the database instance at the second network deployment is authorized based on at least a second data object of the plurality of data objects.

Database replication using a resource management node

Systems, methods, and devices for retrying a query. A method includes receiving a query directed to database data and assigning execution of the query to one or more execution nodes of an execution platform, the one or more execution nodes configured to execute the query on a first version of a database platform. The method includes determining that execution of the query was unsuccessful. The method includes assigning a first retry execution of the query to the one or more execution nodes of the execution platform and determining whether a regression or an intermittent fault caused the execution of the query to be unsuccessful based at least in part on whether the first retry execution of the query was successful or unsuccessful.

Identifying software regressions based on query retry attempts in a database environment

Example resource management systems and methods are described. In one implementation, a system includes a memory and a processing device operatively coupled to the memory. The processing device is to receive a query referencing database data stored in a storage platform, determine a task associated with processing the received query, and create an execution node comprising cache resources and processing resources. Furthermore, a size of the cache resources of the execution node is determined upon creation of the execution node, based at least in part on the task, and processing resources of the execution node are determined upon creation of the execution node, based at least in part on the task. The execution node is included within a plurality of execution nodes to process the task associated with processing the received query.

A system and method for pruning data based on metadata. The method may include receiving a query that includes a plurality of predicates and identifying one or more applicable files including database data satisfying at least one of the plurality of predicates. The identifying the one or more applicable files including reading metadata stored in a metadata store that is separate from the database data. The method further includes pruning inapplicable files including database data that does not satisfy at least one of the plurality of predicates to create a reduced set of files and reading the reduced set of files to execute the query.

Data pruning based on metadata

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Foster City, CA, United States of America

Benoit Dageville