Question

Research Question: Explore history of database systems and discuss the three most important developments in database development history to date. (1.25 marks each)

Note: Use proper references in the APA style. Your research report must be well presented using proper content organization. (1.25 marks)

Answer 1

Answer:-

history of database systems:-

A Database Management System 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 to 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.

Enter the Database Management System (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 their 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) to one record from 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 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 1nd 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 common place. Unstructured data is both non-relational and schema-less, and Relational Database Management Systems simply were not designed to handle this kind of data.

NoSQL

NoSQL (“Not only” Structured Query Language) came about as a response to the Internet and the need for faster speed and the processing of unstructured data. Generally speaking, NoSQL databases are preferable in certain use cases to relational databases because of their speed and flexibility. The NoSQL model is non-relational 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 store and process 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.

discuss the three most important developments in database development history to date

SQL and the Golden Age of Databases

The main feature of these database systems was storing structured data. The introduction of algebra, relational calculus and understandable terms led to the creation of SEQUEL language (Structured English Query Language). Promoting this language to version 2 resulted in the structured query language (SQL). This language was approved in 1987 and established as ISO and ANSI standard. Since the 1970s, thanks to the success of the SEQUEL, query languages were inspired by ideas and theories of E. F. Codd. The Ingres project of University of California at Berkeley and language QUEL resulted in development of another type of database model. It was an object-relational database model, known as Postgres. The Postgres and SQL were connected in 1995 when the QUEL query language interpreter was replaced by SQL language interpreter. In 1996, it was renamed to PostgreSQL language.

Everything to Objects

The development of an object-relational model was closely associated with both implemented models. The structured object model experienced a massive development mainly in the 1990s, although its origin is associated with the period of the golden age of databases. The pressure made on object-oriented programming in the 1990s was transferred to the database world. This was the time of boom for purely object-oriented databases. Communication uses the Object Query Language, which is built over the SQL-92 standard, and the Object Definition Language, which is based on the used programming languages. The ODMG-93 standard is created for definition languages as a superset of more general model, the Common Object Model (COM). Hand in hand with programming with the same language, it also communicates, data from databases are acquired and presented. Using the same language reduces the incidence of errors which may be in the steps of migration from the relational model to objects. The advantage of the object-oriented database management systems is the possibility of a direct expression of the complexity of modelled reality in the database, but more on that next time.

Migration to Unstructured "NoSQL” Databases

At the turn of the millennium, there was a certain shift in the perception of data. Boundaries in approach built on a structured data model (relational/object-oriented model) and object application are emerging. This led to dusting off the idea of unstructured database. This idea originated in the late 1960s. The use of this model, however, was very rare at that time. Today unstructured databases called NoSQL (the NoSQL term was first coined in 1998 by Carlo Strozzi) share only this basic idea. The boom of unstructured databases is associated with the Google. It presented its database proposal called BigTable designed for large amounts of data. This proposal was inspired by the Amazon, which presented its project of unstructured database called Dynamo. These proposals of databases later became the basis for today used NoSQL databases. The biggest difference in these proposals was that the databases were not line-oriented like the SQL databases, but column-oriented. More about the difference between line and column data storage will be dealt with next time