1. New Data Types:
In Older days data types are less, so all the data will fit in tables. Now we have lot new data types, Like: Weblogs, Videos, Images, Sensor data and some 3rd part apps data like (Twitter, FB, LinkedIn...) . To support these new data types, we need big data.
2. Data Space:
Videos and Images will take more hard drive space, in earlier we have only tables. Tables will not take much space, it used to occupy only GBs (1GB=1000 megabytes) or TBs(1TB=1000 gigabytes). But Videos and Images will need more space like Petabytes (1PB=1000 terabytes) of memory . Think about YouTube and Facebook, each day how many images and videos are going to upload and how much space is required for that.
3. Different types of data:
Unstructured data and structured data.
To support Unstructured data we need one, schema less database.
4. Storage cost?
-Since the data is increasing like Petabytes, we have to spend lot of money on space. So we need cheap storage devices.
5. Slow Development cycle:
To develop any application, right now we are using below steps.
Requirement-->Development-->Testing-->Deployment
The main cost difference will come based on the type Development process which we will go.
Current Development modal.
Ex:
Application Design--->Database Design (SQL, MY SQL, Oracle...)--> Application Development (Java, Microsoft, ...)---->Deployment
So if you take Big data, no need to think about "Database Design".
6. Fast growth of users and data.
Ex: Facebook, LinkedIn, Twitter.
All above applications are growing very fast, so handle the database of above applications is not an easy. So the answer is big data.
Answer to all above problems: Big Data
Big Data is evolution of RDBMs
