Unlike Git, however, Noms is written to store structured data instead of text files and support very large data sets.
Relational databases are built for storing structured collections of data that will be queried in a random fashion.
Silk lets you create and store structured information and then filter, visualize and manipulate it in various ways, all without the need to edit code.
Unlike Git, though, Noms focuses on storing structured data (not text files) and is designed to support very large data sets.
Whilst databases storing structured chemical information have proliferated in the last few years, published scientific articles, technical reports, patent documents and other forms of unstructured data remain to be the richest source of the most current information.
Several applications are available for storing structured taxon-based character data in order to generate identification keys and natural language descriptions, and to aggregate them from lower to higher taxa.
This is performed by iteratively parsing the stored structures with increasing time spacing (see Figure 1D).
In this case, we can store structure and content information and still be able to perform categorization/clustering of content, analysis of web site topology, web page ranking, and OLAP analysis of structure and content, among other automation activities.
Since most of the manufacturing systems are controlled by low level controllers (e.g., PLCs, CNCs) they store structure and control logic of the system to be modeled by a DES system.
Events from issue reports are stored as structured data.
