Snowflake. has been granted a patent for a system that facilitates access to relational database information through API operations for dataframes. The system includes electronic storage for input dataframes and processors that translate dataframe queries into relational database operations, generating and presenting results to users. GlobalData’s report on Snowflake gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Snowflake, Social media analytics was a key innovation area identified from patents. Snowflake's grant share as of July 2024 was 65%. Grant share is based on the ratio of number of grants to total number of patents.
Accessing relational database information via api for dataframes
The patent US12072911B1 describes a system and method for accessing information in a relational database through Application Programming Interface (API) operations tailored for dataframes. The system includes electronic storage for an input dataframe, which is structured as a two-dimensional table with ordered rows and columns, complete with row and column labels. The system's processors are programmed to generate a first relation from the input dataframe, defining a schema that outlines attributes and their types. It can then process a dataframe query, translating it into a sequence of relational database operations that yield a second relation, which is also structured with its own schema. This second relation is populated with records corresponding to the results of the query and can be presented to users.
The claims further detail that the API may be sourced from an open-source library and can support various data analysis modalities, including relational and linear algebra operators. The relational database operations adhere to SQL standards and may be executed within a data warehouse environment. The system also includes provisions for schema computation and value computation queries to facilitate the generation of the second relation. Additionally, the output can be converted back into a dataframe format and presented to users through a client computing platform interface, enhancing accessibility and usability of the data stored in the relational database.
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