Processing Structured and Unstructured Data in a NoSQL Database – the Basic Rules

Structured and unstructured data are not an either-or scenario. Instead, it’s a matter of matching the data type to your application and its needs. Each serves a purpose and has advantages and disadvantages.

Get a better idea of when to use structured and unstructured data and some of the benefits of each. 

What is Structured Data?

Structured data generally lives within a relational database. Big data is processed using relational/SQL databases where each field of information is in length-delimited data.

Some data is machine-generated. This might include information from the following sources.

• Satellite imagery that powers weather information or informs military movements
• Scientific information, such as seismic images or space exploration data
• Surveillance photos or video
• Data from sensors, such as traffic or weather data

What’s the Difference Between Structured and Non-structured Data?

The obvious difference is in how and where the data is stored. Unstructured/Non-structured data is generally in a NoSQL database while structured data is in a relational/SQL database. 

But the difference in the experience with the data is in analytics. Data processing programs can provide much deeper analytics for structured data than you can with unstructured but that’s not to say you will have no analytical capabilities with non-structured data.

Emerging tools make it so that unstructured data reacts similarly to structured data, but at much faster speeds with the opportunity to scale quickly. These tools make it possible to analyze sentiments as if they were a black and white piece of data like a ZIP code.

Learn more about how AI is changing NoSQL databases and download BangDB, a NoSQL database that employs machine learning to make unstructured data searchable and usable.