18604990. STORING SEMI-STRUCTURED DATA simplified abstract (Google LLC)

From WikiPatents
Jump to navigation Jump to search

STORING SEMI-STRUCTURED DATA

Organization Name

Google LLC

Inventor(s)

Martin Probst of Munich (DE)

STORING SEMI-STRUCTURED DATA - A simplified explanation of the abstract

This abstract first appeared for US patent application 18604990 titled 'STORING SEMI-STRUCTURED DATA

The abstract of the patent application describes methods, systems, and apparatus for storing semi-structured data. One method involves maintaining multiple schemas, receiving semi-structured data, determining that the data does not match any existing schemas, and then generating a new schema for the data.

  • The innovation involves the dynamic creation of schemas for semi-structured data that does not match existing schemas.
  • The system encodes the data in a new format based on the new schema and stores it in a data repository.
  • This approach allows for the efficient storage and retrieval of diverse types of semi-structured data.

Potential Applications:

  • This technology could be used in database management systems to handle a wide range of semi-structured data formats.
  • It could also be applied in data integration platforms to streamline the processing of heterogeneous data sources.

Problems Solved:

  • Traditional schema-based approaches may struggle to accommodate the variety of semi-structured data formats.
  • This innovation addresses the challenge of efficiently storing and managing diverse data types.

Benefits:

  • Improved flexibility in handling semi-structured data.
  • Enhanced data organization and retrieval capabilities.
  • Streamlined data processing workflows.

Commercial Applications:

  • Database management systems
  • Data integration platforms
  • Big data analytics tools

Questions about the technology: 1. How does this innovation compare to traditional schema-based data storage methods? 2. What are the potential scalability challenges of implementing this technology in large-scale data systems?

Frequently Updated Research: Ongoing research in data management and schema evolution may provide further insights into optimizing the storage and retrieval of semi-structured data.


Original Abstract Submitted

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for storing semi-structured data. One of the methods includes maintaining a plurality of schemas; receiving a first semi-structured data item; determining that the first semi-structured data item does not match any of the schemas in the plurality of schemas; and in response to determining that the first semi-structured data item does not match any of the schemas in the plurality of schemas: generating a new schema, encoding the first semi-structured data item in the first data format to generate the first new encoded data item in accordance with the new schema, storing the first new encoded data item in the data item repository, and associating the first new encoded data item with the new schema.