Teradata’s patented system and method extend compression-aware aggregation logic to column partitioned databases, enabling efficient processing of complex aggregate queries. The method involves generating executable code for evaluating aggregation expressions and performing aggregation on intermediate results using push-down techniques. This innovation enhances query performance on compressed data sources. 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 March 2024 was 77%. Grant share is based on the ratio of number of grants to total number of patents.
Column partitioned database aggregation with compression-aware logic
A recently granted patent (Publication Number: US11899662B1) discloses a computer-implemented method for executing a relational database management system (RDBMS) in a computer system. The method involves managing a relational database with column-partitioned base tables and executing aggregation queries containing SELECT statements with aggregation expressions referencing multiple columns within the table. The RDBMS generates executable code for the queries, evaluates aggregation expressions to generate intermediate results, and performs aggregation using push-down techniques on the intermediate result set within the data storage facility to produce final results.
Furthermore, the method includes features such as the use of Parquet tables, compressed columns, and GROUP-BY clauses referencing compressed columns. The executable code generated by the RDBMS evaluates aggregation expressions, generates hashes for grouping fields, and utilizes push-down aggregation techniques for efficient processing. The patent also covers scenarios where aggregation queries contain predicates and GROUP-BY clauses with compressed grouping columns. Overall, the method optimizes the execution of aggregation queries within a relational database system, enhancing performance and scalability for data processing tasks.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
