Cloud computing is helpful in working with big data and using its power to make better decisions in the interest of one's business. At first glance it seems very complicated to understand the need of unstructured data methods related to the big data world and hence the question is: Why bother creating cloud databases?
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Big data is one of the newest and shiniest able in the IT industry like DevOps, which cannot be ignored easily and cannot be understood easily as well. It is hard because there is no single “BIG DATA” type available in fact, it is a name given to the collective unstructured data which is being collected by today’s technology from various sources.
The discipline of big data analytics is all about getting the best from the large data sets for the sake of business and consumer satisfaction. In this analytics, data scientists work with big data and process it to convert it into useful information.
Any enterprise technical stack is largely dictated by the type of data they need to store which in turn is dictated by the type of business they want to do and its requirements.
RDBMS is good for managing relational and structured data and will continue to be the first choice of many businesses and applications. But in order to handle the large amounts of data being generated by social media, sensor networks and other sources NOSQL technologies better fit the scenario. The size of unstructured data can go up to terabytes and petabytes.
RDBMS data is highly structured, clean and ordered. This makes it highly effective and good for some applications but not so good and effective for others. One big problem with the RDBMS is that when the data sets began to fill the hard disks then queries start thrashing the CPU and RAM and more resources are needed in order to keep the DBMS working. The only way to do this is by scaling up and by investing more in hardware.
And scaling up the resources with a huge budget only solves the resource problem. Other problems like disaster recovery and storing the data where it is needed still persist. If a company or enterprise can rent Google cloud SQL or Amazon RDS these problems will fail to persist.
Theoretically, managing cloud-based big data is very cost-effective and scalable. But, it’s not only good news that is there to it.
The ride is hard for DB administrators. The NoSQL databases have missing schemas and they don’t look like the relational database at all. Besides it is very hard to capture and store the new rivers of data let alone process, report and archive them.
Storing the data in Windows Azure, MongoDB and Amazon simpleDB is just the beginning of the data science which is required to make the most of Big Data.