Structured Query Language (SQL) is a database language designed for managing data held in a relational database management system. SQL was initially developed by IBM in the early 1970s (Date 1986). The initial version, called SEQUEL (Structured English Query Language), was designed to manipulate and retrieve data stored in IBM’s quasi-relational database management system, System R. Then in the late 1970s, Relational Software Inc., which is now Oracle Corporation, introduced the first commercially available implementation of SQL, Oracle V2 for VAX computers.

The SQL data manipulation language (DML) is used to query and modify database data. In this chapter, we will describe how to use the SELECT, INSERT, UPDATE, and DELETE SQL DML command statements, defined below.

One thing that you will most certainly run into at one point or another when working with Microsoft SQL Server, or any other Relational Database Management System (RDBMS), is blocked processes caused by locks on database objects. But what are database locks and why can they sometimes cause one process to block another?

Data aggregation is any process in which information is gathered and expressed in a summary form, for purposes such as statistical analysis. A common aggregation purpose is to get more information about particular groups based on specific variables such as age, profession, or income.

There are two primary processes (1) transaction management and (2) concurrency control in database management system (DBMS):

Transaction management (TM) handles all transactions properly in DBMS. Database transactions are the events or activities such as series of data read/write operations on data object(s) stored in database system (Larson, Blanas, Diaconu, Freedman, Patel, & Zwilling, 2011).

Java Database Connectivity (JDBC) is an application programming interface (API) for the programming language Java, which defines how a client may access a database. It is Java based data access technology and used for Java database connectivity. It is part of the Java Standard Edition platform, from Oracle Corporation. It provides methods to query and update data in a database, and is oriented towards relational databases. A JDBC-to-ODBC bridge enables connections to any ODBC-accessible data source in the Java virtual machine (JVM) host environment.

The data is present in arbitrary order, but the logical ordering is specified by the index. The data rows may be spread throughout the table regardless of the value of the indexed column or expression. The non-clustered index tree contains the index keys in sorted order, with the leaf level of the index containing the pointer to the record (page and the row number in the data page in page-organized engines; row offset in file-organized engines).

A database index is a data structure that improves the speed of data retrieval operations on a database table at the cost of additional writes and storage space to maintain the index data structure.

As we have seen already, database consists of tables, views, index, procedures, functions etc. The tables and views are logical form of viewing the data. But the actual data are stored in the physical memory. Database is a very huge storage mechanism and it will have lots of data and hence it will be in physical storage devices. In the physical memory devices, these data cannot be stored as it is. They are converted to binary format. Each memory devices will have many data blocks, each of which will be capable of storing certain amount of data. The data and these blocks will be mapped to store the data in the memory.

A B+ tree is an N-ary tree with a variable but often large number of children per node. A B+ tree consists of a root, internal nodes and leaves. The root may be either a leaf or a node with two or more children.

Indexes are a common way to enhance database performance. An index allows the database server to find and retrieve specific rows much faster than it could do without an index. But indexes also add overhead to the database system as a whole, so they should be used sensibly.

Query Optimizer Uses heuristic algorithms to evaluate relational algebra expressions. This involves: estimating the cost of a relational algebra expression transforming one relational algebra expression to an equivalent one choosing access paths for evaluating the subexpressions Query optimizers do not optimize just try to find reasonably good evaluation strategies

This command displays the execution plan that the PostgreSQL planner generates for the supplied statement. The execution plan shows how the table(s) referenced by the statement will be scanned — by plain sequential scan, index scan, etc. — and if multiple tables are referenced, what join algorithms will be used to bring together the required rows from each input table.

The notion of functional dependencies is used to define second, and third normal form, and the Boyce-Codd normal form (BCNF). ... Functional Dependencies are fundamental to the process of Normalization Functional Dependency describes the relationship between attributes (columns) in a table.

The systems development life cycle (SDLC), also referred to as the application development life-cycle, is a term used in systems engineering, information systems and software engineering to describe a process for planning, creating, testing and deploying an information system. The systems development lifecycle concept applies to a range of hardware and software configurations, as a system can be composed of hardware only, software only or a combination of both.

A core aspect of software engineering is the subdivision of the development process into a series of phases, or steps, each of which focuses on one aspect of the development. The collection of these steps is sometimes referred to as the software development life cycle (SDLC). The software product moves through this life cycle (sometimes repeatedly as it is refined or redeveloped) until it is finally retired from use. Ideally, each phase in the life cycle can be checked for correctness before moving on to the next phase.

The entity relationship (ER) data model has existed for over 35 years. It is well suited to data modelling for use with databases because it is fairly abstract and is easy to discuss and explain. ER models are readily translated to relations. ER models, also called an ER schema, represented by ER diagrams.

Normalization should be part of the database design process. However, it is difficult to separate the normalization process from the ER modelling process so the two techniques should be used concurrently.

Use an entity relation diagram (ERD) to provide the big picture, or macro view, of an organization’s data requirements and operations. This is created through an iterative process that involves identifying relevant entities, their attributes and their relationships.

One important theory developed for the entity relational (ER) model involves the notion of functional dependency (FD).  The aim of studying this is to improve your understanding of relationships among data and to gain enough formalism to assist with practical database design.