Limitations of Traditional Databases to support Big Data Traditional Databases are not suitable for Big Data because of so many reasons. Some of them are listed below: Traditional Databases – - Finds it challenging to handle such huge data volumes - The majority of the data comes in a semi-structured or unstructured format from social media, audio, video, texts, and emails. Traditional databases can’t categorize unstructured data. They are designed to accommodate structured data. - Traditional Databases lack in high velocity because these are designed for steady data retention rather than rapid growth - Even if traditional databases are used to store and process big data it will turn out to be very expensive.
Being a large organization , the company’s response to changes in the market is slow. IBM also has a weakness in relying on big enterprises. The large businesses are the main customers of IBM of mainframe, services, and software. A fluctuation in the spending of the large enterprise largely affects the sales of the company. Threats Competition is a major threat to IBM.
You will find it difficult to repair your own car and the cost of repairing it is expensive. Even today 's modern cars, maintenance or bug fixes in unexpected situations are a hindrance for many because of their complexity and the amount of money spent on car repairs. Electric cars are similar to traditional cars, requiring high reliability. Many people are wondering what to do when the tram system goes wrong. Repairs can be made easily with a network of dealers or private garages for gasoline and petrol cars, but prices will be as high as regular cars.Increase the cost of electricity monthly user.
Is something trending in social media? Daily, seasonal and event-triggered peak data loads can be challenging to manage. Even more so with unstructured data. Complexity. Today's data comes from multiple sources, which makes it difficult to link, match, cleanse and transform data across systems.
SHORTAGE OF SKILLED MANPOWER As ships expand in size, there is a requirement of efficient equipment to load and unload cargo. Skilled manpower is very much needed in operating these sophisticated equipments. Now shortage of manpower leads to decrease in efficiency and optimal results are not achieved. Even though there have been several moves to setup institutes to train the manpower, the requirement has become significant with the privatisation picking up. GDP/TRADE
Digital Divide – This technology is reducing the geographical boundaries to education. The individuals and various educational and even non-educational organizations can have at their door-step a huge information, world wide educational course ware, irrespective of their location. However, this access to information is not free of cost, further it needs to spend on expensive hardware and software & limitations of ‘Telecommunications’ creates the major hurdles to most of the organizations intending to use ICT. To meet the global needs and to face the global competition, a poor country like Vietnam has also began to obtain the internet access and started implementation of ICT in their educational sector. But, it is increasing the cost of infrastructure for the educational institutes.
Economic factors Being connected to the internet and being able to afford technological devices is very expensive. Users of digital resources must have computer equipment which includes suitable software as well as a connection to the internet. There are many people (big families, people with a low income) who struggle to afford these things and this means that lots of people fall behind as technology increases. Also cost becomes a problem when big businesses e.g. schools have to pay for a lot more broadband access that is fast enough to serve a big network.
Due to continuous increase in the electronic data along with less up-to-date systems cause our data to crash. Lower networks and servers block updating and managing tasks of such data. Having limited storage space causes overloading of data and threatens its preservation. Uncertain and unwanted loss of relevant data needs our data to be sorted, so that ingestion of material data wouldn’t cause
Big Data is also geospatial data, 3D data, audio and video, and unstructured text, including log files and social media. Traditional database systems were designed to address smaller volumes of structured data, fewer updates or a predictable, consistent data structure. Traditional database systems are also designed to operate on a single server, making increased capacity expensive and finite. As applications have evolved to serve large volumes of users, and as application development practices have become agile, the traditional use of the relational database has become a liability for many companies rather than an enabling factor in their business. Big Data databases, such as Mongo DB, solve these problems and provide companies with the means to create tremendous business value.