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Five Database Technology 'Faceoffs' Explained

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To make matters more complex, there are also various types of data that are associated with different database models. Structured data refers to information within a relational database that is highly organized with fixed fields associated with each record or file. Structured data often include dates, numbers and groups of words like those found in a subscriber spreadsheet or retail point-of-sale records.

Unstructured data, in contrast, is data that does not have a predefined data model.  While unstructured data is typically text-based, it can also include numbers and dates — though they are not organized against a preexisting configuration. Some everyday examples of unstructured data include email, text messages and social media posts. Many companies utilize both structured and unstructured data in analyzing business operations, which can be challenging when choosing a database technology platform.

Database technologies are rapidly evolving to a degree where it can be difficult to keep up with the newest solutions and buzzwords, let alone distinguish one from another. Looking for the right solution can be especially challenging when IT vernacular is constantly putting terms at odds. There are countless “this-or-that” conversations in database technology. In this slideshow, Kurt Dobbins, CEO of Deep Information Sciences, takes a look at a few of the most common faceoffs.  

 

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