The paper investigates the main characteristics of SQL and NoSQL, and its comparison in the area of Big Data Analytics. Big Data leading internet companies were the first to use NoSQL databases to get around the problems with relational database management system. The paper aims to investigate on how relational database management systems aren't always the best choice because they can't keep up with the expanding amount of unstructured data. As the amount of data that needs to be processed grows at an exponential rate, NoSQL is a dynamic and cloud-friendly way to process unstructured data easily. IT professionals often argue about whether SQL or NoSQL is better, but NoSQL is becoming the new favorite of the big data movement as business data management is constantly growing. Through the paper there will be a more closer description of the SQL and NoSQL movement, with both the concepts and techniques, and also what is the future of SQL and NoSQL. Data analytics lifecycle will be discused as well as the main big data analysis techniques. Big data analytics process contains a wide variety of information, and has the potential to provide value for businesses. The complexity of big data makes it impossible to manage using the same methods and technologies that have traditionally been used. The paper examines SQL and NoSQL challenges and solutions in the view of Big Data, with the discussion of their advantages and disadvantages. In addition, there is also a discussion in the case study, where is a comparison of most popular SQL and NoSQL databases, which are MySQL and MongoDB.