Skip to document
Welcome to StudocuSign in to access the best study resources
Guest user
0followers
Upload
HomeMy LibraryAsk AI
  • You don't have any recent items yet.
My Library
  • You don't have any courses yet.
  • You don't have any books yet.
  • You don't have any Studylists yet.

A Brief History of Database Management

database management system
Course

Computer science (Csc 231)

14 Documents
Students shared 14 documents in this course
Academic year: 2020/2021
Uploaded by:
Anonymous Student
This document has been uploaded by a student, just like you, who decided to remain anonymous.
Federal College of Education (Special), Oyo

Recommended for you

Comments

Please sign in or register to post comments.

Students also viewed

Related documents

Preview text

A Brief History of Database Management

By Keith D. Foote on October 25, 2021
A database management system (DBMS) allows a person to organize, store, and
retrieve data from a computer. It is a way of communicating with a computer’s “stored
memory.” In the very early years of computers, “punch cards” were used for input,
output, and data storage. Punch cards offered a fast way to enter data and retrieve it.
Herman Hollerith is given credit for adapting the punch cards used for weaving looms to
act as the memory for a mechanical tabulating machine, in 1890. Much later, databases
came along.
Databases (or DBs) have played a very important part in the recent evolution of
computers. The first computer programs were developed in the early 1950s and
focused almost completely on coding languages and algorithms. At the time, computers
were basically giant calculators and data (names, phone numbers) was considered the
leftovers of processing information. Computers were just starting to become
commercially available, and when business people started using them for real-world
purposes, this leftover data suddenly became important.
CONSIDERING A CAREER IN DATA MANAGEMENT?
Learn about the key responsibilities you’ll have and the skills and education you’ll need
with our online training program.
Register Here
Enter the DBMS. A database, as a collection of information, can be organized so a
database management system can access and pull specific information. In 1960,
Charles W. Bachman designed the integrated database system, the “first” DBMS. IBM,
not wanting to be left out, created a database system of its own, known as IMS. Both
database systems are described as the forerunners of navigational databases.
By the mid-1960s, as computers developed speed and flexibility, and started becoming
popular, many kinds of general-use database systems became available. As a result,
customers demanded a standard be developed, in turn leading to Bachman forming the
Database Task Group. This group took responsibility for the design and standardization
of a language called Common Business Oriented Language (COBOL). The Database
Task Group presented this standard in 1971, which also came to be known as the
“CODASYL approach.”
The CODASYL approach was a very complicated system and required substantial
training. It depended on a “manual” navigation technique using a linked data set, which
formed a large network. Searching for records could be accomplished by one of three
techniques:
 Using the primary key (also known as the CALC key)
 Moving relationships (also called sets) from one record to another
 Scanning all records in sequential order
Eventually, the CODASYL approach lost its popularity as simpler, easier-to-work-with
systems came on the market.
Edgar Codd worked for IBM in the development of hard disk systems, and he was not
happy with the lack of a search engine in the CODASYL approach, and the IMS model.
He wrote a series of papers, in 1970, outlining novel ways to construct databases. His
ideas eventually evolved into a paper titled A Relational Model of Data for Large Shared
Data Banks, which described a new method for storing data and processing large
databases. Records would not be stored in a free-form list of linked records, as in
CODASYL navigational model, but instead used a “table with fixed-length records.”
IBM had invested heavily in the IMS model and wasn’t terribly interested in Codd’s
ideas. Fortunately, some people who didn’t work for IBM were interested. In 1973,
Michael Stonebraker and Eugene Wong (both then at UC Berkeley) made the decision
to research relational database systems. The project was called INGRES (Interactive
Graphics and Retrieval System) and successfully demonstrated a relational model could
be efficient and practical. INGRES worked with a query language known as QUEL, in
turn, pressuring IBM to develop SQL in 1974, which was more advanced (SQL became
ANSI and OSI standards in 1986 and 1987). SQL quickly replaced QUEL as the more
functional query language.
RDBM Systems were an efficient way to store and process structured data. Then,
processing speeds got faster, and “unstructured” data (art, photographs, music, etc.)
became much more commonplace. Unstructured data is both non-relational and
schema-less, and relational database management systems simply were not designed
to handle this kind of data.
MySQL
and uses a “distributed” database system. This non-relational system is fast, uses an
ad-hoc method of organizing data, and processes high volumes of different kinds of
data.
“Not only” does it handle structured and unstructured data, it can also process
unstructured big data, very quickly. The widespread use of NoSQL can be connected to
the services offered by Twitter, LinkedIn, Facebook, and Google. Each of these
organizations stores and processes colossal amounts of unstructured data. These are
the advantages NoSQL has over SQL and RDBM Systems:
 Higher scalability
 A distributed computing system
 Lower costs
 A flexible schema
 Can process unstructured and semi-structured data
 Has no complex relationship
Unfortunately, NoSQL does come with some problems. Some NoSQL databases can be
quite resource-intensive, demanding high RAM and CPU allocations. It can also be
difficult to find tech support if your open-source NoSQL system goes down.
NoSQL Data Distribution
Hardware can fail, but NoSQL databases are designed with a distribution architecture
that includes redundant backup storage of both data and function. It does this by using
multiple nodes (database servers). If one, or more, of the nodes goes down, the other
nodes can continue with normal operations and suffer no data loss. When used
correctly, NoSQL databases can provide high performance at an extremely large scale,
and never shut down. In general, there are four kinds of NoSQL databases, with each
having specific qualities and characteristics.
Document Store Databases
Document stores save each record, and associated data, in a single document.
Individual documents contain semi-structured data which can be queried using various
query tools. A document store (often called a document-oriented database), manages,
stores, and retrieves semi-structured data (also known as document-oriented
information). It is often used with other non-relational database formats. Documents can
be described as independent units that improve performance and make it easier to
spread data across a number of servers. Document stores typically come with a
powerful query engine and indexing controls that make queries fast and easy. Examples
of document stores include Mongo DB and Amazon Dynamo DB.
Document-oriented databases store all information for a given “object” within the
database, and each object in storage can be quite different from the others. This makes
it easier for mapping objects to the database and makes document storage for web
programming applications very attractive. (An “object” is a set of relationships. An article
object could be related to a tag [an object], a category [another object], or a comment
[another object].)
Graph Data Stores
Graph databases came about in 2006, when Tim Bernes-Lee established the concept of
a large database that “linked data.” Location-aware systems, routing and dispatch
systems, and social networks are the primary users of graph databases (also called
graph data stores). These databases are based on graph theory and work well with data
that can be displayed as graphs. They provide a very functional, cohesive picture of big
data.
They differ from relational databases, and other NoSQL databases, by storing data
relationships as actual relationships. This type of storage for relationship data results in
fewer disconnects between an evolving schema and the actual database. It has
interconnected elements, using an undetermined number of relationships between
them. Examples graph databases include Neo4j, GraphBase, and Titan.
Polyglot Persistence
Polyglot Persistence is a spin-off of “polyglot programming,” a concept developed in
2006 by Neal Ford. The original idea promoted applications be written using a mix of
languages, with the understanding that a specific language may solve a certain kind of
problem easily, while another language would have difficulties. Different languages are
suitable for tackling different problems.
Many NoSQL systems run on nodes and large clusters. This allows for significant
scalability and redundant backups of data on each node. Using different technologies at
each node supports a philosophy of polyglot persistence. This means “storing” data on
multiple technologies with the understanding certain technologies will solve one kind of
problem easily, while others will not. An application communicating with different
database management technologies uses each for the best fit in achieving the end goal.
Intelligent Databases
An intelligent database manages, not simple data, but information. It presents the
information in a natural way that is useful and informative. The concept was introduced
in the book “Intelligent Databases” in 1989 by Mark Chignell, Setrag Khoshafian,
Kamran Parsaye, and Harry Wong. They applied three levels of intelligence:
 High-level tools
 The user interface
 The database engine

o o

 UML

o o o o o o o o

 Python

o o o o o o

 Web Dev

o o o o o o o o o o o

 Tutorial

o o o o o o o

#######  Compilers

o o o o o o o o

o

o

o

o

 Blogs

Hospital Management

System Database Design

September 25, 2019 by adones evangelista

ER Diagram for Hospital

Management System

This Hospital Management System Database Design has an ER Diagram for

Hospital Management System project. This material includes database

schema, Data dictionaries, Database Tables and ERD.

What is Hospital Management System Database Design?

 Manage Outpatient
This table will be used for storing and managing the inpatient
information and diagnosis.
 Manage Room
This table will be used for storing and managing the room information
and assigning of patient in every room.
 Manage Bills
The billing table will be used for managing the statement of accounts
per patient and for the collection of bills.

ER Diagram for Hospital Management

System with Relationship

This section will show you the ER Diagram for Hospital Management
System Project. In the image below you see the actual relationship of all
entity.

Diagram of Hospital Management

System

Figure 8: Proposed SCA Hospital Management System Entity
Relationship Diagram
Based on figure 8, the proposed er diagram for hospital management
system with relationship shows the entity of the proposed SCA Hospital
Management system database, which is presented by tables; the tables are
made to meet the required specification of the system and provide much more
specific details of each entity within the system.
Table 1: tblPatient

####### Field Name Description Type Length

####### patient_id (PK) Patient ID varchar 10

####### name Patient Name varchar 50

####### patient_id (FK) Patient ID varchar 10

####### doctor_id (FK) Doctor ID varchar 10

####### date Laboratory Date Date/Time 10

####### amount Amount of Lab int 20

Table 4: tblInpatient

####### Field Name Description Type Length

####### patient_id (PK) Patient ID varchar 10

####### room_no (FK) Room Number varchar 50

####### date_of_adm Date of Admission Date/Time 10

####### date_of_dis Date of Discharge Date/Time 10

####### lab_no (FK) Laboratory Number varchar 10

Table 5: tblOutpatient

####### Field Name Description Type Length

####### patient_id (PK) Patient ID varchar 10

####### date Date of Outpatient varchar 10

####### lab_no (FK) Laboratory Number varchar 20

Table 6: tblRoom

####### Field Name Description Type Length

####### room_no (PK) Room Number varchar 50

####### room_type Room Type varchar 50

####### status Status Of Room varchar 20

Table 7: tblBill

####### Field Name Description Type Length

####### bill_no (PK) Patient ID int 11

####### patient_id (FK) Patient Name varchar 10

####### doctor_charge Patient Age int 10

####### room_charge Patient Gender int 10

####### no_of_days Patient Address int 10

####### lab_charge Patient Disease int 10

####### bill Doctor ID int 10

Was this document helpful?

A Brief History of Database Management

Course: Computer science (Csc 231)

14 Documents
Students shared 14 documents in this course

University: Federal College of Education (Special), Oyo

Was this document helpful?
A Brief History of Database Management
By Keith D. Foote on October 25, 2021
A database management system (DBMS) allows a person to organize, store, and
retrieve data from a computer. It is a way of communicating with a computer’s “stored
memory.” In the very early years of computers, “punch cards” were used for input,
output, and data storage. Punch cards offered a fast way to enter data and retrieve it.
Herman Hollerith is given credit for adapting the punch cards used for weaving looms to
act as the memory for a mechanical tabulating machine, in 1890. Much later, databases
came along.
Databases (or DBs) have played a very important part in the recent evolution of
computers. The first computer programs were developed in the early 1950s and
focused almost completely on coding languages and algorithms. At the time, computers
were basically giant calculators and data (names, phone numbers) was considered the
leftovers of processing information. Computers were just starting to become
commercially available, and when business people started using them for real-world
purposes, this leftover data suddenly became important.
CONSIDERING A CAREER IN DATA MANAGEMENT?
Learn about the key responsibilities you’ll have and the skills and education you’ll need
with our online training program.
Register Here
Enter the DBMS. A database, as a collection of information, can be organized so a
database management system can access and pull specific information. In 1960,
Charles W. Bachman designed the integrated database system, the “first” DBMS. IBM,
not wanting to be left out, created a database system of its own, known as IMS. Both
database systems are described as the forerunners of navigational databases.

Students also viewed

Related documents