CS403 GDB Solution Spring 2022
Due Date: 31 Aug 2022
Question
With the emergence of Big Data and cloud technologies, the volume, variety, and velocity of data is growing exponentially with time. The exponential growth and heterogeneity of data needs not only distributed and scalable architecture but also needs such structures that can store different forms of data in an efficient way and can store not only the structured data as well as semi-structured and unstructured data. In your opinion, do you think that relational databases are suitable in the above scenario? Justify your answer with solid reasons.
Solution
RDBMS work with structured data. Relationships in the system have constraints, which promotes a high level of data integrity. You can't store unstructured (text, music, documents, videos etc) data into rdbms. It doesn't matter if its small or big data. You have much better options in that scenario as mentioned in other answers.
NoSQL.
Limitations of RDBMS to support "big data"
First, the data size has increased tremendously to the range of petabytes. RDBMS finds it challenging to handle such huge data volumes. To address this, RDBMS added more central processing units (or CPUs) or more memory to the database management system to scale up vertically.
Second, the majority of the data comes in a semi-structured or unstructured format from social media, audio, video, texts, and emails. However, the second problem related to unstructured data is outside the purview of RDBMS because relational databases just can't categorize unstructured data. Relational databases are not designed for change. Data in relational databases is arranged in rows and columns, with each row representing a unique entry and each column describing unique attributes. Data modeling must be done in advance and can take months or even years, depending on the system. Changes after the fact are time- and resource-intensive, and databasemodeling projects can take many years and cost millions of dollars. Big data is constantly changing, requiring a database platform that is flexible and forgiving. Unstructured data, typically categorized as qualitative data, cannot be processed and analyzed via conventional data tools and methods. Since unstructured data does not have a predefined data model, it is best managed in non-relational (NoSQL) databases.
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