Structuring unstructured big data

Relational databases which use SQL have a long- standing position in most organizations and have dominated the database markets for a long time. Relational databases work best with structured data—such as a set of sales figures—which readily fits in well-organized tables. This is not the case with unstructured data, such as that found in word-processing docu- ments, social media, log files etc. Especially in large scale and high concurrency applications, such as search engines and Social media using the relational database to store and query dynamic user data has been found to be inadequate. The advent of Big Data created a need for out-of-the-box horizontal scalability for data management systems. This ushered in an array of choices for Big Data Management under the umbrella term NoSQL, new technology for storage of large unstructured data. NoSQL databases are today gaining importance due to their linear scalability, schema flexibility and comparatively higher performance This paper highlights the implementation of NoSQL databases. It seeks to analyze various solutions to structure the unstructured data in terms of the way data is stored and retrieved from NoSQL databases.