Basics - A Historical Perspective
- File Systems v/s DBMS
- Data Models
- Levels of Abstraction
- Structure of DBMS
- Database Design
- Database Design
- ER Diagrams
- Attributes
- Entity
- Relationships
- Additional Features of the ER Model
- Relational Model
- Introduction to the Relational Model
- Integrity constraint over relations
- Enforcing Integrity Constraints
- Querying Relational Data
- Views
- Relational Algebra
- Tuple Relational Calculus
- SQL
- Form of basic SQL query
- UNION
- INTERSECT
- EXCEPT
- Aggregation Operators
- Complex Integrity Constraints in SQL
- Triggers and Active data bases
- Schema Refinement
- Problems caused by redundancy
- Decompositions and its problems
- Functional Dependencies and its reasoning
- Introduction to Normal Forms
- First Normal Form (1NF)
- Second Normal Form (2NF)
- Third Normal Form (3NF)
- Boyce-Codd Normal Form (BCNF)
- Fourth Normal Form (4NF)
- Fifth Normal Form (5NF or PJNF)
- Sixth Normal Form (6NF)
- Transaction
- Transaction Concept
- Transaction State
- Implementation of Atomicity and Durability
- Concurrent Executions
- Serializability
- Recoverability
- Implementation of Isolation
- Lock Based Protocols
- Timestamp Based Protocols
- Validation Based Protocols
- Multiple Granularity
- Recovery and Atomicity in dbms
- Recovery with Concurrent Transactions
- Indexing
- Data on External Storage
- File Organization and Indexing
- Cluster Indexes
- Primary Indexes
- Secondary Indexes
- Index data Structures
- Comparison of File Organizations, Indexes and Performance Tuning
- Indexed Sequential Access Methods
- Dynamic Index Structure - B+ Tree
A Historical Perspective
Database Management Systems (DBMS) have been around for several decades, and their history can be traced back to the early 1960s. In the early days, computer systems were designed to manage data in a hierarchical or navigational manner, where data was stored in a tree-like structure. This method of storing data was inefficient and difficult to use, as it required a lot of manual effort to access and manage the data.
In the late 1960s, The first general-purpose DBMS, designed by Charles Bachman, was called the Integrated Data Store (IDS) which was based on network data model for which he was received the Turing Award (The most prestigious award which is equivalent to Nobel prize in the field of Computer Science.).
In the late 1970s, Mr Edgar Codd proposed a new data representation framework called the Relational Database Model. Mr Edgar Codd won the 1981 Turing Award for his seminal work. This model was based on the concept of a table, with rows representing individual records and columns representing individual fields within those records. The relational model allowed for more efficient storage and retrieval of data and was easier to use than the hierarchical or navigational models.
In the late 1980s IBM developed the Structured Query Language (SQL) for relational databases, as a part of R project. This system was designed to manage large amounts of data and was used primarily in corporate and government applications. SQL was adopted by the American National Standards Institute (ANSI) and International Organization for Standardization (ISO).
In the 1980s, several new DBMS products were introduced, including Oracle, Sybase, and Microsoft SQL Server. These systems were designed to be more user-friendly and to support more advanced data modeling and query languages.
In the 1990s, object-oriented DBMS (OODBMS) emerged, which were designed to store and manage complex data structures, such as multimedia and other types of non-traditional data. These systems were initially popular in research and academic environments, but their adoption was limited in the commercial sector.
In the 1991, Microsoft ships MS access, a personal DBMS and that displaces all other personal DBMS products.
In the 1997, XML applied to database processing. Many vendors begin to integrate XML into DBMS products.
In the 2000s, web-based applications and cloud computing became more popular, and DBMS systems began to adapt to these new technologies. New DBMS systems were developed to support distributed and web-based applications, including NoSQL databases such as MongoDB and Cassandra.
Today, DBMS systems continue to evolve, with an emphasis on scalability, performance, and support for cloud-based applications. Some of the most popular DBMS systems in use today include Oracle, Microsoft SQL Server, MySQL, PostgreSQL, and MongoDB.
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