Part 1: 180-200 words with references

Topic Question:

What is NoSQL DB and what is its difference from RDB?

Discussion Post:

NoSQL is a term used to describe high-performance, non-relational databases. NoSQL databases utilize a variety of data models, including document, graph, key-value, and columnar. NoSQL databases are widely recognized for ease of development, scalable performance, high availability, and resilience.

NoSQL databases disrupted the database market by offering a more flexible, scalable, and less expensive alternative to relational databases.

They also were built to better handle the requirements of Big Data applications.

NoSQL databases differ from older, relational technology in four main areas:

Data models: A NoSQL database lets you build an application without having to define the schema first unlike relational databases which make you define your schema before you can add any data to the system. No predefined schema makes NoSQL databases much easier to update as your data and requirements change.

Data structure: Relational databases were built in an era where data was fairly structured and clearly defined by their relationships. NoSQL databases are designed to handle unstructured data (e.g., texts, social media posts, video, email) which makes up much of the data that exists today.

Scaling: It's much cheaper to scale a NoSQL database than a relational database because you can add capacity by scaling out over cheap, commodity servers. Relational databases, on the other hand, require a single server to host your entire database. To scale, you need to buy a bigger, more expensive server.

Development model: NoSQL databases are open source whereas relational databases typically are closed source with licensing fees baked into the use of their software. With NoSQL, you can get started on a project without any heavy investments in software fees upfront.

Reference:

NoSQL Vs Relational Databases. (n.d.). Retrieved February 15, 2018, from https://www.mongodb.com/scale/nosql-vs-relational-databases
Critical Reply with reference:

Part 2: 180-200 words with references

Topic Question:

Can you define what Big Data is? Why has it been buzz word past 10 years?

Discussion Post:

Big data is a fairly new term for an old concept. It is essentially a term that describes data collected from all sources, including internal and external data. The intimidation of big data sometimes stems from the name itself because of the fact that such a large concept is trying to be implemented but with the right tools and techniques the concept of big data can be further resolved. The concept itself has received more traction in the not so distant past but has truly been a subject since the 1980's.

Due to the improvement of computers and storage along with the complexity of data as technology improves the concept or term of big data continues to be at the forefront. One of the largest issues with big data is the analytics of the data itself. There is plenty of big data that is constantly being collected and the issue there is that the data is either not being analyzed or not being analyzed quick enough.

Having big data available and having it analyzed can make a large difference to any company that collects data (virtually all companies) by helping with decision making. Data analysis from big data allows a business to be more profitable along with being more efficient in business practices and business decisions. Getting that collected data, while it benefits companies and has been around for a long time, is still a concept that has not been fully developed and still requires more development to fully get confidence behind big data.