Categories of NoSQL Databases

This document discusses the four basic categories of NoSQL databases: key value store, document based store, column based store, and graph based store. It explains the differences between these categories and provides examples of each. The document also includes references for further reading.

Running head: CATEGORIES OF NOSQL DATABASES
Categories of NoSQL databases
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1CATEGORIES OF NOSQL DATABASES
1. List and discuss four basic categories of NoSQL databases
There are four basic categories of NoSQL databases which are categorized as shown:
Key value store–It consisted of big hash table of keys as well as standards.
Document based store- It is stored of documents which are completed up of tagged
basics.
Column based store- Each of the storage space block is contained data as of one
column.
Graph based – The network database is used boundaries as well as nodes for
representing as well as storing of data (Eshtay, Sleit, &Aldwairi, 2019).
2. Difference between categories and provide examples
Key value store NoSQL database: The examples of this NoSQL database are Riak
and Amazon S3. The schema less format of this input value database such as Riak is
required for storage requirements.The key values are used hash table anywhere there is
existence of exclusive key as well as indicator to specific piece of data. The bucket is
such logical group of keys excluding they are not actually grouping the data (Chen&Lee,
2019). In order to interpret a value, there is required to identify key as well as bucket as
real key is hash (key + bucket).
Document store NoSQL database: This type of data is such a compilation of key
value pairs which are consisted document store as same as key value store. The
differentiation is that the ethics are recorded and provided structure as well as encoded
managed data. Apache as well as CouchDB are examples of the document store.
JavaScript is such a query language by means of MapReduce as well as HTTP. The

2CATEGORIES OF NOSQL DATABASES
document style databases are schema less which can make added fields to the documents
as a proper task with no such defined changes first.
Column store NoSQL database: Into the column oriented NoSQL database, the data
are being recorded into cells grouped into columns of data in place to rows of data. The
columns are being set into column families. It contains unrestricted digit of columns
which can create at the runtime as well as description of schema. Read as well as write is
done by means of columns rather than the rows (Atzeni et al., 2016). The examples of
column store NoSQL database is HBase and Cassandra. Relational DBMS is stored into
rows, the benefit of this type of storing into columns is faster search as well as access plus
data aggregation.
Graph based NoSQL database: By this nature of NoSQL database, there is no finding
of rigid arrangement of SQL as well as tables in addition to also columns representations.
There is proper representation of the data by means of address of scalability concerns.
The graphs are used into edges and nodes which can offer index free adjacency. The data
are being transformed from one of the model to other by means of Graph Base NoSQL
database. The example is Neo4J. By means of edges as well as nodes, there is storage of
data (Vera, et al., 2015). The nodes are prepared by relations with an additional that is
being presented by edges among the nodes. Both the nodes along with relations consisted
defined possessions.

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References
Atzeni, P., Bugiotti, F., Cabibbo, L., &Torlone, R. (2016). Data modeling in the NoSQL
world. Computer Standards & Interfaces.
Chen, J. K., & Lee, W. Z. (2019). An Introduction of NoSQL Databases Based on Their
Categories and Application Industries. Algorithms, 12(5), 106.
Eshtay, M., Sleit, A., &Aldwairi, M. (2019). IMPLEMENTING BI-TEMPORAL
PROPERTIES INTO VARIOUS NOSQL DATABASE
CATEGORIES. International Journal of Computing, 18(1), 45-52.
Vera, H., Boaventura, M. W., Holanda, M., Guimaraes, V., & Hondo, F. (2015, September).
Data modeling for NoSQL document-oriented databases. In CEUR Workshop
Proceedings (Vol. 1478, pp. 129-135).