ECM38IS.1: Database Management Trends, Technology, Innovation

This report delves into the evolving landscape of database management, exploring current trends, technological advancements, and innovative ideas. It examines data optimization in data warehouses, the role of in-memory technology in big data, and the implications of converged and disruptive technologies. The report highlights technologies like GitHub and RESTful APIs, crucial for database administrators. Through a secondary data analysis, the report addresses key research questions concerning new database technologies, advancements in PostgreSQL, the impact of in-memory technology on NoSQL, MongoDB's security measures, the viability of new technologies, and the priorities of database administrators. It provides a theoretical framework, reviews relevant literature, and discusses trends like converged databases, disruptive databases, MongoDB security, and big data trends, including in-memory innovation and predictive analysis. The report aims to provide a comprehensive overview of the database management field, offering valuable insights for both students and professionals.

Database Management Trend Technology and Innovation
Database Management Trend Technology and
Innovation
Subtitle as needed (paper subtitle)
Authors Name/s per 1st Affiliation (Author)
line 1 (of Affiliation): dept. name of organization
line 2: name of organization, acronyms acceptable
line 3: City, Country
line 4: e-mail address if desired
Authors Name/s per 2nd Affiliation (Author)
line 1 (of Affiliation): dept. name of organization
line 2: name of organization, acronyms acceptable
line 3: City, Country
line 4: e-mail address if desired
Abstract—This report indicates various trends in database
management system, enhancement in technology in database as
well as innovative ideas in database administration. Trends in
data optimization in data warehouse, In-Memory technology in
big data has been discussed. Technologies like converged and
disruptive technologies has been described with enough details.
Technologies like Github, RestFul APIs that database
administrator must understand to cope up with future
advancement. This report is created using secondary data
analysis method. The purpose of this report is identifying various
niche of database management and giving proper introduction to
those niche.
Keywords-database, dbms, database administrator, converged,
data, in memory, trends, database technology
I. INTRODUCTION
Database technologies are consist of two types of data,
structured and unstructured. As per database definition, raw
data irrespective of its nature can be stored in one location
from where data can be processed. Database management
system is the gateway to the database. As the world is moving
to electronic/digital platforms, the need of storing more data is
increasing significantly. However, many organizations are
acquiring millions of data in one day alone. Just storing data is
not the concern any more [1]. Various trends and technologies
are emerging that facilitates the process of storing data as well
as accessing those data from database. Need for super
computers that can handle processing of millions of data
cannot be fulfilled by all organizations. Because super
computers are extremely expensive. That is why organizations
tend to enhance their database or data center environment as
per latest trend. Often, organizations use various tools and
technologies that facilitates the data processing task. Database
administrators take a very important role in managing these
databases. From assigning roles and privileges to tracking
activities of database system is crucial for database
administrator. As technologies are evolving, various methods
ate generated to collect and store data [4]. Database
administrator must get knowledge about enhancement in ideas
regarding database management to understand existing loop
holes and keep the data center efficient all the time.
II. PROBLEM SPECIFICATION
A. Problem Specification
At present organizations are moving to cloud or using in-
house systems to store their data. No matter which option an
organization chooses, if amount of data is in millions and
billions then cost of data storage will be extremely high.
Organizations are also facing issues with data protection.
Cyber threats like DDoS, Malicious code injection and many
more are affecting the database system. Database hold all the
information, from critical business data to customer credit card
details. If all these data are stolen then organization can lose its
reputation and integrity. Moreover, managing data centers are
crucial for any business. Database administrator must have
proper understanding of responsibilities and roles to fulfill. In
spite of being very efficient in work, database administrator
must have proper understanding of new ideas of database
administrative work. This is because emerging technologies
and rising threats of cyber security.
B. Importance of Research
Research can be considered as a tool for constructing
knowledge and facilitate learning process. If a fact in one
particular article can be found in another article, it can be
surely said that fact is effective and accurate. Therefore,
research helps in assuring accuracy of data collected from
secondary sources. Considering only one view point is not an
optimal approach. Each view point has its benefits and
drawbacks. Multiple viewpoints can be collected and
understood from different article and sources. Evaluating all
the viewpoints will ensure what is required to considered and
to what extension. Research helps in collecting more facts that
ultimately result in better informative source. Diverse ways of
understanding a topic can be found through research. From the
above analysis, it is clear that report can have robust and
accurate data if research is done. Different ideas of database
administration related topics can be compared to understand
importance of all the ideas. New enhancement technologies in
database management can be found easily. Moreover, if
research is properly done then impact of that technology as
well as its future implications can also be understood.

Database Management Trend Technology and Innovation
C. Research Questions
i. What is new in database technology?
ii. What advancements can be seen in PostgreSQL?
iii. Is In-Memory technology can improve NoSQL
capability?
iv. Is MongoDB capable of implementing enough security
measures to protect data?
v. Will new technologies like converged and disruptive
technology be enough to replace Big-Data requirements?
vi. What are the ideas that database administrators look for
this year?
III. THEORETICAL FRAMEWORK
Database management systems are evolving each year.
Need for storing more data is pushing organizations to innovate
more technologies than never before. Many organizations uses
various trends that helps them manage their database system
effectively and efficiently. In this year both the old and new
technologies can be seen in practice. In order to implement
better and faster database management data centers must be
integrated with newer technologies. These technologies can be
costly and may have hard learning curve. That is why
organizations can apply various trends to facilitate the data
management process with available resources or adding
minimal resources. Trends like data warehouse optimization
and graph databases are very popular and giving high end
results. PostgreSQL is one of the based relational database
management systems for using in datacenters. It has all the
features of a relational database as well as some features of
NoSQL database. PostgreSQL is very suitable for data analysis
works. If PostgreSQL advancements can incorporate
performance like NoSQL and support some of horizontal
scalability then there would be no question of thinking of any
other database management system. In memory technology is
one of the most popular topics that organizations are focusing
on to make the data processing faster. If properly implemented,
then in-memory technology will make systems much faster.
Need for implementing costly hardware for improve processing
each year will be reduced by half.
In general, various database management technologies
innovations should be considered as important. Database
innovations can create new windows for organizations to get
into new environment where everything can be managed
easily. However, considering only one innovative technology is
not right approach. Two technologies should be identified,
analyzed and new information generated to get accurate
knowledge. As organizations are moving to cloud, relies on
collaboration and often test new technologies, database
administrators must get ideas of these things so that no matter
what happened data center is always efficient and protected.
IV. LITERATURE REVIEW
A. New Database Technologies
Data warehouse optimization is the process of increasing
the performance of database systems in data center.
Organization can increase performance of the data center by 80
percent. To adjust and disentangle their RDBMS, database
directors and managers will relocate these frameworks to the
cloud, on the off chance that they have not done so as of now.
DATAVERSITY found around 46 percent of members in an
examination plan on utilizing cloud-based social databases in
the following year or two.
B. PostgreSQL Advancements:
Latest PostgreSQL version has OmniDB debugger. It
allows creating SQL procedures that can execute full
transaction management. This allows developers to generate
more dynamic server side programs. Automating server side
scripts is much easier with OmniDB debugger. Partitioning
evaluation from PostgreSQL 9 to 11 is now supported. This
implies that PostgreSQL provides great features in terms of
version update [3]. Updating the data base version becomes
easy with PostgreSQL. PostgreSQL now provide better
parallelism, partitions and stored procedures. Creating scalable
and dynamic backed services is much accurate and easy in
PostgreSQL. pgAdmin is one the best and comparatively new
GUI tool for PostgreSQL. It is considered to be one of the best
in relational databases UI tools. It supports complex queries
and provide extensive support to data center operators.
pgAdmin is continuously evolving and adding new rich
features to its environment. The PostgreSQL Security Audit
administration from 2ndQuadrant can assist you with
protecting your information from outside dangers. Get tips on
cutting edge malware insurance systems for your undertaking,
tending to vulnerabilities, and how to forestall security
ruptures.
Figure 1: Popularity of PostgreSQL
C. New Database Trends
Converged Database: It is possible to place everything
within a single database offering. No architectural reason can
be found for not having a database that provides tunable
consistency model equipped with strict ACID properties at one
end and consistency style model at the other end. A database
should support relational compliance but extensible schema

Database Management Trend Technology and Innovation
through permitting information being represented broadly
through a relational model. However, database should support
application-extensible schemas such as JSON data types.
Database must be compatible with various languages as well as
application program interfaces. A pluggable data storage
should allow database management to store physical data as
row and columnar data like B-Tree as column. Database should
support consistency characteristics and distributed availability.
TABLE 1: REQUIREMENTS FOR DIRECT DEAL
DISTRIBUTION BETWEEN PRODUCER AND
CONSUMER OF MUSCAT AGRO PRODUCTS
Functional
Classificatio
n
Function
Details
Detail Requirements
Member
Data
Define the
needed
membership
data through the
transaction
entity
All the details of
customer that are
required to perform
various actions
Product
Data
Define the
product data
Display product list to
consumers and making
purchasing decisions
Transaction
Data
Define all order
processing
information
Complete an order based
on defined business rules
and objectives
Disruptive Database: Extrapolating existing advances is a
valuable interest, and is frequently the main prescient system
accessible. Be that as it may, history instructs us that advances
don't generally proceed upon a current direction. Problematic
advances rise which make discontinuities that can't be
extrapolated and can't generally be completely envisioned. It's
conceivable that a problematic new database innovation is
inescapable, yet all things considered, the enormous changes
in database innovation that have happened inside the most
recent decade speak to as a lot of progress as we can
undoubtedly acknowledge [5]. That having been stated, there
are a couple of processing innovation patterns which stretch
out past database engineering and which may encroach
intensely on the databases of things to come.
D. MongoDB Security:
As per new computing environments, data security has
become one of the major factors in database management
system. NoSQL means no security does not work in current
situation even if computation efficiency is very high. That is
MongoDB has added various security features over the years to
make its environment secure. The commercial version of
MongoDB provides enterprise level security. Enterprise
version opf MongoDB has Kerberos and LDAP authentication,
Red Hat Identity Management Certification standards that
fulfills the strict security policy. MongoDB with advance
security features can quickly identify, defend and staunchly
control access to organization data. Currently MongoDB has
five core security features such as authentication, authorization,
encryption, auditing and governance.
E. Big Data Trends:
In-memory innovation stores the information in RAM
rather, which is many, ordinarily quicker. A report from
Forrester Research figures that in-memory information texture
will develop 29.2 percent every year. One of the innovations
that organizations are examining trying to speed their
enormous information handling is in-memory innovation. In a
conventional database, the information is put away
frameworks furnished with hard drives or strong state drives
(SSDs).
Figure 2: Classification of the most extended (Apache-
based) distributed processing back-ends for big data
analytics
Prescient examination is firmly identified with machine
learning; truth be told, ML frameworks frequently give the
motors to prescient investigation programming. In the
beginning of big data examination, associations were glancing
back at their data to perceive what occurred and afterward
they began utilizing their investigation instruments to research
why those things occurred. Prescient examination goes above
and beyond, utilizing the big data investigation to foresee what
will occur later on [2]. The quantity of associations utilizing
prescient examination today is shockingly low—just 29
percent as per a 2016 review from PwC. Notwithstanding,
various merchants have as of late turn out with prescient
investigation apparatuses, so number could soar in the coming
a long time as organizations become progressively mindful of
this integral asset.
TABLE 2: MongoDB Workloads
Workload Description Type
Word Count Reads a txt file and calculate
occurrence of each word
one pass,
IO-bound
Grep Extract similar strings from
txt files and calculates
occurrence count
one pass,
IO-bound
PageRank Calculate the significance of
each vertex within a graph
one pass,
IO-bound
F. Database Administrator Ideas:
First thing that Database Administrators must be
researching about is GitHub. GitHub was initially designed as
version control system. Currently it is the biggest collaborative
platform. Various developers uses GitHub to upload their

Database Management Trend Technology and Innovation
projects. It is the biggest source of technology related data. If
organization is using GutHub as collaborative platform, then
Database administrators must have idea of it.
Services related RESTful have developed to turn into the
true route for PCs to interoperate over the web. Realizing how
to utilize Services related RESTful makes it simpler to impart
database tasks to a wide range of different applications and
gadgets. At the point when an organization needs to share
information in different configurations, from populating an
Excel document to sending instant messages or associating
with a gadget like a voice right hand, Services related
RESTful are the best approach.
When a DBA comes outside the database and connects with
the improvement world, the individual in question will run
into Environment of Docker. Docker is an incredibly
mainstream approach to bundle all the administrations around
an application into a holder that permits the application to run
unmodified on a designer's PC, a mutual test server, or an
open cloud, including Oracle Cloud. It assists ventures with
building a lithe programming conveyance pipeline to transport
new highlights quicker.
V. EMPIRICAL ANALYSIS TECHNIQUES
In order to complete the report, secondary data analysis has
been used. Mainly research papers and articles has been used
for data collection. Some organization data has also been
collected to current trends. In this report no data has been
collected directly. Data collected and analyzed by other people
has been used in this report. Both the qualitative and
quantitative data has been used to create the report. All the
patent free and current research articles has been used.
VI. KEY FINDINGS
Though SQL is the primary language for communicating
with database, supplementary graph languages should be
supported by Databases. REST based document-style queries.
The database application should support identifying level of
consistency and availability. With the improvement in SQL
databases, notably PostgreSQL, the SQL databases are again in
the verge of dominating database industry. More, organizations
are considering PostgreSQL for data analysis because of its
secure environment and rich features. New scalable databases
that fully embraced SQL. In terms of security in MongoDB,
enterprise version has to be purchased. Which makes
MongoDB costly option in comparison with PostgreSQL.
VII. CONCLUSIONS
From the above study it can be concluded that SQL is
becoming more popular again. New features and better data
management approaches are enhancing its capabilities. The
Database administrator must have knowledge of things that
programmers use to under everything better. Entire report is
created with the purpose of showing the current status of
database management system. Both the SQL and NoSQL
databases has been discussed in detail in this report.
REFERENCES
[1] [1]F. Bhaswara, R. Sarno and D. Sunaryono, "Perbandingan
Kemampuan Database NoSQL dan SQL dalam Kasus ERP Retail",
Jurnal Teknik ITS, vol. 6, no. 2, 2017. Available:
10.12962/j23373539.v6i2.24031.
[2] [2]Á. Vathy-Fogarassy and T. Hugyák, "Uniform data access platform
for SQL and NoSQL database systems", Information Systems, vol. 69,
pp. 93-105, 2017. Available: 10.1016/j.is.2017.04.002.
[3] [3]C. Niyizamwiyitira and L. Lundberg, "Performance Evaluation of
SQL and NoSQL Database Management Systems in a Cluster",
International Journal of Database Management Systems, vol. 9, no. 6,
pp. 01-24, 2017. Available: 10.5121/ijdms.2017.9601.
[4] [4]K. Mahmood, "Performance Comparison of NOSQL Database
Cassandra and SQL Server for Large Databases", Journal of Independent
Studies and Research - Computing, vol. 14, no. 2, 2016. Available:
10.31645/jisrc/(2016).14.2.0003.
[5] [5]A. Khalil Jumaa, "Secured Data Conversion, Migration, Processing
and Retrieval between SQL Database and NoSQL Big Data", Diyala
Journal For Pure Science, vol. 14, no. 4, pp. 66-87, 2018. Available:
10.24237/djps.1404.449a.