Stephen E. Arnold: Relational Big Data Stores Versus Hierarchical Databases

Advanced Cyber/IO
Stephen E. Arnold
Stephen E. Arnold

Relational Data Stores Versus Hierarchical Databases

The article titled Codd’s Relational Vision – Has NoSQL Come Full Circle on opensource connections relates the history of relational databases and applies their lessons to the NoSQL databases so popular today. The article walks through the simplest databases that followed the hierarchical model and then into generalized databases. The article then delves into the work of Edgar F. Codd himself:

“When Codd wrote his paper, he criticized the DBTG databases of the day around the area of how the application interacted with the databases abstractions. Low-level abstractions leaked into user applications. Application logic became dependent on aspects of the databases: Specifically, he cites three criticisms: access dependencies… order dependencies… index dependencies… Codd proposed to get around these limitations by focusing on a specific abstraction: relations…. In short, Codd created a beautiful abstraction that turned out to be reasonable to implement.”

Then came the decision to build horizontally scalable systems, which were incompatible with Codd’s abstraction. The article ultimately suggests that the smart way to approach a database is to base it off of your needs, not off of what is currently trending. There is even a Contact us link for readers who aren’t sure what type of database to select, hierarchical or relational.

Chelsea Kerwin, January 01, 2014

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Phi Beta Iota: What is missing right now from the Internet are persistent URLs for all data elements; a citation analytic index that cannot be corrupted by Google’s whims; and varied forms of free and fee access to all information in all languages all the time. Humans, not algorithms, are the ultimate definers of relations. The industrial era information and intelligence industries are retarded — unwilling to think new thoughts — and all too addicted to archaic forms of production and profit.

See Also:

Big Data @ Phi Beta Iota

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