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Table 1.2 shows a comparison between data mining and big data.

Table 1.1 Differences in the attributes of big data and RDBMS.

ATTRIBUTES	RDBMS	BIG DATA
Data volume	gigabytes to terabytes	petabytes to zettabytes
Organization	centralized	distributed
Data type	structured	unstructured and semi‐structured
Hardware type	high‐end model	commodity hardware
Updates	read/write many times	write once, read many times
Schema	static	dynamic

Table 1.2 Data Mining vs. Big Data.

S. No.	Data mining	Big data
1)	Data mining is the process of discovering the underlying knowledge from the data sets.	Big data refers to massive volume of data characterized by volume, velocity, and variety.
2)	Structured data retrieved from spread sheets, relational databases, etc.	Structured, unstructured, or semi‐structured data retrieved from non‐relational databases, such as NoSQl.
3)	Data mining is capable of processing large data sets, but the data processing costs are high.	Big data tools and technologies are capable of storing and processing large volumes of data at a comparatively lower cost.
4)	Data mining can process only data sets that range from gigabytes to terabytes.	Big data technology is capable of storing and processing data that range from petabytes to zettabytes.