Datadog. has been granted a patent for a monitoring system that de-duplicates data for database storage. The method involves mapping unique fields and values to index values, generating structured vectors, and storing these vectors to optimize data representation and reduce redundancy in subsequent messages. GlobalData’s report on Datadog 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 Datadog, Hybrid cloud mgmt was a key innovation area identified from patents. Datadog's grant share as of July 2024 was 59%. Grant share is based on the ratio of number of grants to total number of patents.
Data de-duplication method for database storage
The patent US12050576B2 outlines a method and system for de-duplicating data in a database, focusing on efficient storage and retrieval of messages containing various fields and field values. The method begins by associating a block of memory with a specific time period and receiving messages from multiple computing systems. It determines whether the fields or field values of these messages are already present in a first mapping table. If not, it generates new entries in this table, creating unique index values for each field or field value. Subsequently, a first vector is created to represent these fields and their values, which is then ordered to reflect the message structure. A second mapping table is also generated to associate the ordered index values with a structure index value, leading to the creation of a second vector that deduplicates subsequent messages by representing them efficiently in memory.
Additionally, the patent describes further enhancements to the de-duplication process, including the generation of a third vector that incorporates a template index value and a binary representation of field value presence. The system is designed to respond to queries by searching the mapping tables and analyzing vectors to determine if the queried data is present. It also includes mechanisms for managing memory, such as deleting older vectors and entries when a memory threshold is exceeded. The method allows for the efficient handling of messages with similar structures but differing field values, ensuring that data storage remains optimized while facilitating quick access and retrieval based on user queries.
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