Teradata. has filed a patent for a method and apparatus to optimize queries in a relational database management system (RDBMS) by leveraging correlations between data columns and partitioning attributes in a cloud-based store. The system eliminates unnecessary data retrieval by mapping predicates to partitioning attributes. GlobalData’s report on Teradata 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 Teradata, Zero Knowledge Proof was a key innovation area identified from patents. Teradata's grant share as of January 2024 was 76%. Grant share is based on the ratio of number of grants to total number of patents.
Optimizing queries in a cloud-based relational database management system
The patent application (Publication Number: US20240012826A1) describes a computer-implemented method for optimizing queries in a relational database management system (RDBMS) when retrieving data from a cloud-based store. The method involves mapping predicates on data columns in queries to partitioning attributes of the data retrieved from the cloud-based store, using semantic correlations. These correlations are defined in formulas or lookup data structures, allowing for efficient data elimination during query processing. The method also includes provisions for manual definition of semantic correlations, exception handling, and output granularity, as well as autonomous or semi-autonomous creation of mappings based on dataset scanning.
Furthermore, the patent application extends to a computer-implemented apparatus and a computer program product embodying the described method. The apparatus includes an RDBMS executing in a computer system, retrieving data from a cloud-based store, and optimizing queries based on semantic correlations. The computer program product comprises program instructions executable by a computer system to perform the method of optimizing queries in an RDBMS when retrieving data from a cloud-based store. Overall, the patent application introduces a novel approach to query optimization in RDBMS by leveraging semantic correlations between data columns and partitioning attributes, enhancing the efficiency of data retrieval and processing from cloud-based storage systems.
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