System Analysis and Modelling in Agriculture Sector

Running Head: SQL and NoSQL in Agriculture sector
SQL AND NOSQL IN AGRICULTURE
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Table of Contents
Introduction:....................................................................................................................................2
Importance of SQL in the agriculture sector:..................................................................................2
Importance of NoSQL in the agriculture sector:.............................................................................4
Difference between SQL and NoSQL:............................................................................................6
RDBMS or NoSQL database for agriculture sector:.......................................................................7
Conclusion:......................................................................................................................................8
References:....................................................................................................................................10

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Introduction:
Agriculture is one of the main aspects of economic growth. There are many benefits of
ensuring data quality that is used by different experts to support their activity, such as monitoring
and planning methods. To mitigate the challenges in agriculture sectors, many types of database
is used. To understand complex agriculture ecosystems, people are using many advanced
technologies like big data and different types of databases. Modern technologies can
continuously monitor the physical environments. Most advanced technologies produce a large
amount of unpredictable data. By using big data analysis, different companies and farmers can
abstract the value from large datasets. With the help of this method, they can increase their
productivity. This technique is not only used in agriculture to store every detail, it is also used in
most of the big industries. Most of the countries are trying to implement this feature ion agriculture.
The aim of this report is to perform a critical review of current technologies and different
research in agriculture sector, which employs the recent practice of big data, SQL and NoSQL, and
analysis, to solve various problems (Hu et al., 2018).. The definition of data quality can be different,
and it can be subjective. Data quality can be seen in the form of multi-dimensional concept.
Importance of SQL in the agriculture sector:
This is one of the serious concerns when a person choosing a database in the agriculture
sector (Kumar and Menakadevi, 2017). Most of the people facing many confusing when they are
choosing a database type, and often that decision swings between NoSQL and SQL. SQL is
famous in this sector for decades. But recently, NoSQL is gaining popularity.
SQL is dominating the agriculture sector for several decades and still using it in this
sector (Woodard, 2016). SQL has better interaction between the data and a user. Before SQL
data is not interactive, and without any interaction, data is useless. SQL is consistent, and it

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allows a user to apply their knowledge while developing a database for agriculture. A farmer can
get support from third-party tools and add-ons. This is a versatile and scalable language and
helps to solve different types of problems. It can be used for scan-intensive deep analytics in big
data technologies (Zhao and Guo, 2018).. SQL is accurate in data storage and representation.
Few SQL systems can support the JASON data format and other different structure object
format.
Some essential benefits of using SQL system in agriculture are discussed below:
SQL support interaction:
SQL is one of the declarative query language. Farmers can build their database as they
want. SQL databases can use an algorithm that can assemble internally and provides the
requested results. But NoSQL support procedural query technique. It requires a user to provide
the exact needs, but also, they need to provide how to produce the result.
The declarative query language is comparatively easy to use for every person. This kind
of database will help to analytics, manages, and operates many business operations.
Standardized SQL:
Sometimes many vendors specify and introduce the SQL languages to their application
interface. SQL is consistent, and it has its additional specifications, such as JDBC and ODBC,
and it is widely available. These features can enable an ecosystem and operator tool that can
monitor, inspect, explore, design and develop various agriculture applications that are based on
SQL system (WANG, WU and LI, 2017)..
Not only farmers, but other people can also reuse their UI knowledge and API in the
multiple backend systems, to reduce the application development time. Standardization provide a