Database Reference
In-Depth Information
Chapter 2. Database and Data
Management
If you're planning to use Hadoop, it's likely that you'll be managing lots of data, and in addi-
tion to MapReduce jobs, you may need some kind of database. Since the advent of Google's
BigTable, Hadoop has an interest in the management of data. While there are some relational
SQL databases or SQL interfaces to HDFS data, like Hive, much data management in Ha-
doop uses non-SQL techniques to store and access data. The
NoSQL Archive
lists more than
150 NoSQL databases that are then classified as:
▪ Column stores
▪ Document stores
▪ Key-value/tuple stores
▪ Graph databases
▪ Multimodel databases
▪ Object databases
▪ Grid and cloud databases
▪ Multivalue databases
▪ Tabular stores
▪ Others
NoSQL databases generally do not support relational join operations, complex transactions,
or foreign-key constraints common in relational systems but generally scale better to large
amounts of data. You'll have to decide what works best for your datasets and the information
you wish to extract from them. It's quite possible that you'll be using more than one.
This topic will look at many of the leading examples in each section, but the focus will be on
the two major categories: key-value stores and document stores (illustrated in
Figure 2-1
)
.
