Database Reference
In-Depth Information
Big data's existence can be traced back to the mid 1990s. However, the actual shift
began in the early 2000s. The evolution of the Internet and mobile technology opened
many doors for more people to participate and share data globally. This resulted in
massive data production, in various formats, flowing across the globe. A wider distrib-
uted network resulted in incremental data growth. Due to this massive data generation,
there is a major shift in application development and many new domain business pos-
sibilities have emerged, like:
•
Social trending
•
OLAP and Data mining
•
Sentiment analysis
•
Behavior targeting
•
Real-time data analysis
With high data growth into peta/zeta bytes, challenges like scalability and man-
aging data structure would be very difficult with traditional relational databases. Here
big data and NoSQL technologies are considered an alternative to building solutions. In
today's scenario, existing business domains are also exploring the possibilities of new
functional aspects and handling massive data growth simultaneously.
NoSQL Ecosystem
NoSQL, often called “Not Only SQL,” implies thinking beyond traditional SQL in a
distributed way. There are more than 150 NoSQL databases available today. The fol-
lowing are a few popular databases:
•
Columnar databases, such as Cassandra & HBase
•
Document based storage like MongoDB & Couchbase
•
Graph based access like Neo4J & Titan Graph DB
•
Simple key-value store like Redis & Couch DB
With so many options and categories, the most important question is, what, how,
and why to choose! Each NoSQL database category is meant to deal with a specific set
of problems.
Specific technology for specific requirement
paradigm is leading the
current era of technology. It is certain that a single database for all business needs is
