Database Reference
In-Depth Information
databases are not good at. All these new storage technologies fall under the umbrella term
NoSQL
.
Note
Although the NoSQL name stuck, it doesn't accurately reflect the nature of the movement,
giving the (wrong) impression that it's against SQL as a concept. A better name would
probably be
nonrelational databases
,as the relational/nonrelational paradigm was the sub-
ject of discussion, whereas SQL is just a language used with relational technologies.
The NoSQL movement was born as an acknowledgment that new technologies were re-
quired to cope with the data changes. Neo4j, and graph databases in general, are part of the
NoSQL movement, together with a lot of other, more or less related storage technologies.
With the rapid developments in the NoSQL space, its growing popularity, and a lot of dif-
ferent solutions and technologies to choose from, anyone new coming into the NoSQL
world faces many choices when selecting the right technology. That's why in this section
we'lltrytoclarifythecategorizationofNoSQLtechnologiesandfocusontheapplicability
of each category. In addition, we'll explain the place of graph databases and Neo4j within
NoSQL.
1.6.1. Key-value stores
Key-value stores represent the simplest, yet very powerful, approach to handling high-
volume concurrent access to data. Caching is a typical key-value technology. Key-value
stores allow data to be stored using very simple structures, often in memory, for very fast
access even in highly concurrent environments.
The data is stored in a huge hash table and is accessible by its key. The data takes the form
of key-value pairs, and the operations are mostly limited to simple
put
(write) and
get
(read)operations.Thevaluessupportonlysimpledatastructuresliketextorbinarycontent,
although some more recent key-value stores support a limited set of complex data types
(for example, Redis supports lists and maps as values).
