DATA CLEAN ROOMS USING DEFINED ACCESS

    公开(公告)号:US20250111083A1

    公开(公告)日:2025-04-03

    申请号:US18977758

    申请日:2024-12-11

    Applicant: Snowflake Inc.

    Abstract: In an embodiment, a data platform creates an application in a data-provider account. The application includes one or more APIs corresponding to one or more underlying code blocks. The data platform shares provider data with the application in the data-provider account, and also installs, in a data-consumer account, an application instance of the application. The application instance includes one or more APIs corresponding to the one or more APIs in the application in the data-provider account. The data platform shares consumer data with the application instance in the data-consumer account, and invokes one or more of the APIs of the application instance to execute respective associated underlying code blocks, which are not visible to the data-consumer account. The data platform also saves output of the one or more respective associated underlying code blocks locally within the data-consumer account.

    Projection constraints in a query processing system

    公开(公告)号:US11928157B2

    公开(公告)日:2024-03-12

    申请号:US17934814

    申请日:2022-09-23

    Applicant: Snowflake Inc.

    CPC classification number: G06F16/90335

    Abstract: A constraint system enforces projection constraints on data values stored in specified columns of a shared dataset when queries are received by a database system. A projection constraint identifies that the data in a column may be restricted from being projected (e.g., presented, read, outputted) in an output to a received query, while allowing specified operations to be performed on the data and a corresponding output to be provided. For example, the projection constraint may indicate a context for a query that triggers the constraint, such as based on the user that submitted the query. Enforcing projection constraints on queries received at the database system allows for data to be shared and used anonymously by entities to perform various operations without the need to tokenize the data.

    SHARING MATERIALIZED VIEWS IN MULTIPLE TENANT DATABASE SYSTEMS

    公开(公告)号:US20230418818A1

    公开(公告)日:2023-12-28

    申请号:US18463904

    申请日:2023-09-08

    Applicant: Snowflake Inc.

    CPC classification number: G06F16/24539

    Abstract: Systems, methods, and devices for sharing materialized views in multiple tenant database systems. A method includes defining a materialized view over a source table that is associated with a first account of a multiple tenant database. The method includes defining cross-account access rights to the materialized view to a second account such that that second account can read the materialized view without copying the materialized view. The method includes modifying the source table for the materialized view. The method includes identifying whether the materialized view is stale with respect to the source table by merging the materialized view and the source table.

    Data clean rooms using defined access

    公开(公告)号:US11803432B1

    公开(公告)日:2023-10-31

    申请号:US18051457

    申请日:2022-10-31

    Applicant: Snowflake Inc.

    CPC classification number: G06F9/547 G06F9/541 G06F16/2456 G06F21/6254

    Abstract: In an embodiment, a data platform creates an application in a data-provider account. The application includes one or more APIs corresponding to one or more underlying code blocks. The data platform shares provider data with the application in the data-provider account, and also installs, in a data-consumer account, an application instance of the application. The application instance includes one or more APIs corresponding to the one or more APIs in the application in the data-provider account. The data platform shares consumer data with the application instance in the data-consumer account, and invokes one or more of the APIs of the application instance to execute respective associated underlying code blocks, which are not visible to the data-consumer account. The data platform also saves output of the one or more respective associated underlying code blocks locally within the data-consumer account.

    DATA CLEAN ROOMS USING DEFINED ACCESS WITH HOMOMORPHIC ENCRYPTION

    公开(公告)号:US20230177210A1

    公开(公告)日:2023-06-08

    申请号:US18162506

    申请日:2023-01-31

    Applicant: Snowflake Inc.

    CPC classification number: G06F21/6245 G06F21/53 G06F2221/032

    Abstract: A data platform creates an application in a data-provider account, where the application includes one or more application programming interfaces (APIs) corresponding to one or more underlying code blocks. The data platform shares homomorphically encrypted provider data with the application in the data-provider account. The data platform installs, in a data-consumer account, an application instance of the application. The data platform shares homomorphically encrypted consumer data with the application instance in the data-consumer account. The data platform invokes one or more of the APIs of the application instance to execute respective associated underlying code blocks, which are not visible to the data-consumer account, and which operate on the shared homomorphically encrypted provider data and the shared homomorphically encrypted consumer data. The data platform saves homomorphically encrypted output of the one or more respective associated underlying code blocks locally within the data-consumer account.

    Framework for providing intermediate aggregation operators in a query plan

    公开(公告)号:US11620287B2

    公开(公告)日:2023-04-04

    申请号:US16939750

    申请日:2020-07-27

    Applicant: Snowflake Inc.

    Abstract: The subject technology receives a query plan, the query plan comprising a set of query operations, the set of query operations including at least one aggregation. The subject technology analyzes the at least one aggregation to generate a modified query plan, the modified query plan including at least a top aggregation operator, an intermediate aggregation operator, and a bottom aggregation operator. The subject technology performs, with respect to the intermediate aggregation operator, at least one operation comprising: the subject technology receives an input intermediate data type; the subject technology performs an internalize operation on the input intermediate data type to generate an internal state; the subject technology performs an accumulate operation on the internal state to generate intermediate data; and the subject technology performs an externalize operation on the intermediate data to generate an output data type.

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