This document discusses the history and evolution of relational databases from the 1960s to present. It describes early hierarchical and network database models, the introduction of relational databases by Edgar Codd in the 1970s, the development of SQL and database management systems, and the rise of applications driving more complex databases. It also outlines the growth of NoSQL databases and how relational databases are incorporating features like support for semi-structured data, columnar storage, hybrid transactional/analytical processing, and distributed SQL to remain relevant in modern data architectures.
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Editor's Notes
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.
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.
The network model is a database model conceived as a flexible way of representing objects and their relationships. Its distinguishing feature is that the schema, viewed as a graph in which object types are nodes and relationship types are arcs, is not restricted to being a hierarchy or lattice.
The network model was adopted by the CODASYL Data Base Task Group in 1969 and underwent a major update in 1971. It is sometimes known as the CODASYL model for this reason. A number of network database systems became popular on mainframe and minicomputers through the 1970s before being widely replaced by relational databases in the 1980s.
IMS DB is a DBMS that helps you organize business data with both program and device independence.
Hierarchical databases and data manipulation language (DL/I calls) are at the heart of IMS DB. Data within the database is arranged in a tree structure, with data at each level of the hierarchy related to, and in some way dependent upon, data at the higher level of the hierarchy. Figure 1 shows the hierarchical database model. In a hierarchical database, data is stored within the database only once. The data item is then available to any user who is authorized to use it. Users do not need to have personal copies of the data.
When people speak of true databases -- they often refer to more structured electronic databases such as relational databases, object databases, OLAP databases, and spatial databases. These kinds of databases can trace their roots back to the 1970 when E.F. Codd from IBM introduced the idea of relational model of databases in his paper entitled "A Relational Model of Data for Large Shared Banks". Before that time most business databases were based on the network model or simple flat file structure.
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.
The main advantage of a relational database is its formally described, tabular structure, from which data can be easily stored, categorized, queried, and filtered without needing to reorganize database tables. Further benefits of relational databases include:
Scalability: New data may be added independent of existing records.
Simplicity: Complex queries are easy for users to perform with SQL.
Data Accuracy: Normalization procedures eliminate design anomalies.
Data Integrity: Strong data typing and validity checks ensure accuracy and consistency.
Security: Data in tables within a RDBMS can limit access to specific users.
Collaboration: Multiple users can access the same database concurrently.
Ray Boyce
Don Chamberlain
The SQL programming language was first developed in the 1970s by IBM researchers Raymond Boyce and Donald Chamberlin. The programming language, known then as SEQUEL, was created following the publishing of Edgar Frank Todd's paper, "A Relational Model of Data for Large Shared Data Banks," in 1970.
In his paper, Todd proposed that that all data in a database be represented in the form of relations. It was based on this theory that Boyce and Chamberlin came up with SQL. In the book "Oracle Quick Guides (Cornelio Books 2013)," author Malcolm Coxall writes that the original SQL version was designed to manipulate and retrieve data stored in IBM's original relational database management systems known as "System R."
It wasn't until several years later, however, that the SQL language was made available publicly. In 1979, a company called Relational Software, which later became Oracle, commercially released its own version of the SQL language called Oracle V2.
Since then, the American National Standards Institute (ANSI) and the International Standards Organization have deemed the SQL language the standard language in relational database communication. While major SQL vendors do modify the language to their desires, most base their SQL programs off of the ANSI approved version.
The SQL programming language was originally developed on the basis of tuple relational calculus and relational algebra. The major components of this language include the following:
Data definition language
Data manipulation language
Data Control Language.
The areas within which SQL programming language can be used include data insertion, update, query, and delete, data access control, and modification and creation of schema. Even though SQL programming language is regarded as a declarative language to a great extent, but it also consists of some procedural elements.
Data Definition Language (DDL)
DDL changes the structure of the table like creating a table, deleting a table, altering a table, etc.
All the command of DDL are auto-committed that means it permanently save all the changes in the database.
Data Query Language
DQL is used to fetch the data from the database.
Data Manipulation Language (DML)
DML commands are used to modify the database. It is responsible for all form of changes in the database.
The command of DML is not auto-committed that means it can't permanently save all the changes in the database. They can be rollback.
Data Control Language
DCL commands are used to grant and take back authority from any database user.
Transaction Control Language
TCL commands can only use with DML commands like INSERT, DELETE and UPDATE only.
These operations are automatically committed in the database that's why they cannot be used while creating tables or dropping them.
Popping up of many database solutions you know of today
https://searchsqlserver.techtarget.com/definition/database-management-system
the DBMS essentially serves as an interface between databases and end users or application programs, ensuring that data is consistently organized and remains easily accessible.
Popping up of many database solutions you know of today
Block = general purpose
Sphere = built for a specific purpose
SQL is the second most popular language among developers
Due to several factors:
SQLite is the most popular relational database in the world due to its use as an embedded database
Because SQL is a declarative language it has been modified to handle all kinds of new features, functionality, and data storage techniques.