🛢DBMS: Cardinality (Definitions)

 "The classification of a relationship; for example, one-to-many, many-to-many, and so on." (Owen Williams, "MCSE TestPrep: SQL Server 6.5 Design and Implementation", 1998)

"The number of tuples (rows) in a relationship. For example, a relationship can be one-to-one, one-to-many, or many-to-many." (Microsoft Corporation, "Microsoft SQL Server 7.0 Data Warehouse Training Kit", 2000)

"The number of unique values for a given column in a relational table. Low cardinality refers to a limited number of values, relative to the overall number of rows in the table." (Ralph Kimball & Margy Ross, "The Data Warehouse Toolkit 2nd Ed ", 2002)

"Cardinality denotes the maximum number of occurrences of one entity that can be related to another entity. Usually, these are expressed as “one” or “many.” Change Data Capture Change data capture is a technique for propagating only changes to source data through the data acquisition process." (Claudia Imhoff et al, "Mastering Data Warehouse Design", 2003)

"The number of distinct values in a column of a table." (Bob Bryla, "Oracle Database Foundations", 2004)

"The cardinality of a relationship represents the number of occurrences between entities. An entity with a cardinality of one is called a parent entity, and an entity with a cardinality of one or more is called a child entity." (Sharon Allen & Evan Terry, "Beginning Relational Data Modeling" 2nd Ed., 2005)

"The number of distinct values taken on by an attribute." (Christopher Adamson, "Mastering Data Warehouse Aggregates", 2006)

"The number of tuples in a relation." (S. Sumathi & S. Esakkirajan, "Fundamentals of Relational Database Management Systems", 2007)

"A representation of the minimum and maximum allowed number of values for an attribute. In semantic object models, written as L.U where L and U are the lower and upper bounds. For example, 1.10 means an attribute must occur between 1 and 10 times." (Rod Stephens, "Beginning Database Design Solutions", 2008)

"A relationship in a data model denoting how many instances of one entity class can be related to an instance of another entity class - zero, one, or many." (Danette McGilvray, "Executing Data Quality Projects", 2008)

"The measure of the number of elements within a set of values. For example, the set A = { 2, 4, 6 } contains 3 elements, and has a cardinality of 3." (MongoDb, "Glossary", 2008)

"In relationships, the characteristic  of a relationship that specifies the upper and lower bounds of how many instances of one entity or object type can be related to each instance of the same or some other entity or object type. Cardinality is separately specified at each end of the relationship. At each end the choices are 0, 1, or M. Combining the cardinality at both ends of a binary relationship, yields 3 x 9 - 1 = 8 possibilities (0:0 is not a valid option)." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"The number of entities or members in a set." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"The number of entities that can exist on each side of a relationship." (Microsoft, "SQL Server 2012 Glossary", 2012)

"The number of occurrences that may exist between a pair of entities. Another way of looking at cardinality is as the number of entity occurrences applicable to a specific relationship. Sometimes the term degree is used instead of cardinality. An alternate usage of the term cardinality within the realm of database administration is a database statistic used by the relational optimizer defining the number of occurrences of a value within a column (or set of columns)." (Craig S Mullins, "Database Administration", 2012)

"The number of rows that is expected to be or is returned by an operation in an execution plan. Data has low cardinality when the number of distinct values in a column is low in relation to the total number of rows." (Oracle, "Database SQL Tuning Guide Glossary", 2013)

"The number of occurrences of two units of data that participate in a relationship" (Daniel Linstedt & W H Inmon, "Data Architecture: A Primer for the Data Scientist", 2014)

"The cardinality of a relationship is the number of instances that can be associated with each entity type in a relationship." (Robert J Glushko, "The Discipline of Organizing: Professional Edition, 4th Ed", 2016)

"The number of rows in a database table or the number of elements in an array. See also associative array." (Sybase, "Open Server Server-Library/C Reference Manual", 2019)

🛢DBMS: Second Normal Form [2nd NF] (Definitions)

"The second normal form (2NF) requires that all attributes be dependent on the whole key. To attain 2NF, the entity must be in 1NF and every nonprimary attribute must be dependent on the entire primary key for its existence. 2NF further reduces possible redundancy in the data model by removing attributes that are dependent on part of the key and placing them in their own entity." (Claudia Imhoff et al, "Mastering Data Warehouse Design", 2003)

"A relation schema R is in 2NF if every nonprime attribute A in R is fully functionally dependent on the primary key of R." (S. Sumathi & S. Esakkirajan, "Fundamentals of Relational Database Management Systems", 2007)

"A table is in 2NF if it is in 1NF and every field that is not part of the primary key depends on every part of the primary key." (Rod Stephens, "Beginning Database Design Solutions", 2008)

"Data is said to be in the second normal form if it complies with the first normal form and has one or more columns in a table that uniquely identify each row." (Robert D. Schneider and Darril Gibson, "Microsoft SQL Server 2008 All-In-One Desk Reference For Dummies", 2008)

"A table is in second normal form (2NF) if and only if each non-key attribute (data item) is fully dependent on the primary key, that is either the left side of every functional dependency (FD) is a primary key or can be derived from a primary key." (Toby J Teorey, ", Database Modeling and Design" 4th Ed, 2010)

"In relational theory, the second of Dr. Codd’s constraints on a relational design: Each attribute must depend on the entire primary key." (David C Hay, "Data Model Patterns: A Metadata Map", 2010)

"The second stage in the normalization process in which a relation is in 1NF and there are no partial dependencies (dependencies in only part of the primary key)." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management" 9th Ed., 2011)

"An entity is in second normal form if and only if it is in first normal form and every non-key attribute is fully dependent on the key." (Craig S Mullins, "Database Administration", 2012)

"The second level of normalization for a table in a relational database. A table is in 2NF if:" (Rod Stephens, "Beginning Software Engineering", 2015)

🛢DBMS: Denormalization (Definitions)

"The technique of placing data often accessed/used together in a physical location that optimizes the performance of the system." (Margaret Y Chu, "Blissful Data ", 2004)

"An intentional violation of the rules of normalization done to increase performance of a database. It typically occurs in varying degrees during all phases of physically implementing a database. Database designs are often denormalized to accomplish a specific performance-related goal. Denormalization can’t be done without a thorough understanding of the data and the needs of the customer." (Sharon Allen & Evan Terry, "Beginning Relational Data Modeling" 2nd Ed., 2005)

"The process of adding planned redundancy to an already fully normalized data model." (Thomas Moore, "EXAM CRAM™ 2: Designing and Implementing Databases with SQL Server 2000 Enterprise Edition", 2005)

"The technique of placing normalized data in a physical location that optimizes the performance of the system." (William H Inmon, "Building the Data Warehouse", 2005)

"Most often the opposite of normalization, more commonly used in data warehouse or reporting environments. Denormalization decreases granularity by reversing normalization, and otherwise." (Gavin Powell, "Beginning Database Design", 2006)

"Organization of data by minimizing joins between tables and storing redundant values in a single table to reduce query time." (Reed Jacobsen & Stacia Misner, "Microsoft SQL Server 2005 Analysis Services Step by Step", 2006)

"The process of adding planned redundancy to an already fully normalized data model." (Thomas Moore, "MCTS 70-431: Implementing and Maintaining Microsoft SQL Server 2005", 2006)

"Denormalization is the process of combining tables so that they are easier to query. Denormalization is opposite to normalization. Denormalization is done to improve query performance." (S. Sumathi & S. Esakkirajan, "Fundamentals of Relational Database Management Systems", 2007)

"The formal process of introducing redundancy back into the database design to improve performance." (Victor Isakov et al, "MCITP Administrator: Microsoft SQL Server 2005 Optimization and Maintenance (70-444) Study Guide", 2007)

"Denormalization is the process of extracting data from normalized tables in the relational model of a data warehouse." (Robert Nisbet et al, "Handbook of statistical analysis and data mining applications", 2009)

"The consolidation of database tables to increase performance in data retrieval (query), despite the potential loss of data integrity. Decisions on when to denormalize tables are based on cost/benefit analysis by the DBA." (Toby J Teorey, ", Database Modeling and Design 4th Ed", 2010)

"A process by which a table is changed from a higher level normal form to a lower level normal form. Usually done to increase processing speed. Potentially yields data anomalies." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management" 9th Ed, 2011)

"Undoing the effect of normalization; the process of putting one fact in numerous places in the database." (Craig S Mullins, "Database Administration", 2012)

"The intentional duplication of columns in multiple tables to increase data redundancy. Denormalization is sometimes used to improve performance." (Sybase, "Open Server Server-Library/C Reference Manual", 2019) 

🛢DBMS: Transaction Log File (Definitions)

"A system table (syslogs) in which all changes to the database are recorded." (Karen Paulsell et al, "Sybase SQL Server: Performance and Tuning Guide", 1996)

"A reserved area of the database in which all changes to the database are recorded. The transaction log is stored in the Syslogs system table and is used by SQL Server during automatic recovery." (Patrick Dalton, "Microsoft SQL Server Black Book", 1997)

"A reserved area set aside for each database on the SQL Server that records all changes diat are made to die database. This enables SQL to recover a database if system problems are encountered." (Owen Williams, "MCSE TestPrep: SQL Server 6.5 Design and Implementation", 1998)

"A file or set of files containing a record of a database's transactions." (Microsoft Corporation, "SQL Server 7.0 System Administration Training Kit", 1999)

"A file or set of files containing a record of the modifications made in a database." (Thomas Moore, "EXAM CRAM™ 2: Designing and Implementing Databases with SQL Server 2000 Enterprise Edition", 2005)

"Transactions in SQL Server are written to the transaction log before they are written to the database. This log information is used primarily for database recovery in the event of a disaster." (Joseph L Jorden & Dandy Weyn, "MCTS Microsoft SQL Server 2005: Implementation and Maintenance Study Guide - Exam 70-431", 2006)

"A file containing a record of database changes." (S. Sumathi & S. Esakkirajan, "Fundamentals of Relational Database Management Systems", 2007)

"File that records transactional changes occurring in a database, providing a basis for updating a master file and establishing an audit trail." (S. Sumathi & S. Esakkirajan, "Fundamentals of Relational Database Management Systems", 2007)

"A file-system–based, internal database construct that records data and table modifications, making it possible to restore information to its previous state should the application roll back a transaction." (Robert D. Schneider and Darril Gibson, "Microsoft SQL Server 2008 All-In-One Desk Reference For Dummies", 2008)

"A file used by the database management system to record all database transactions. The log file is used for recovery of the database in case of failures." (Paulraj Ponniah, "Data Warehousing Fundamentals for IT Professionals", 2010)

"A feature used by the DBMS to keep track of all transaction operations that update the database. The information stored in this log is used by the DBMS for recovery purposes." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management 9th Ed", 2011)

"A collection of records describing the sequence of events that occur during DBMS execution to be used for database recovery in the event of a DBMS failure." (Craig S Mullins, "Database Administration: The Complete Guide to DBA Practices and Procedures" 2nd Ed., 2012)

"A file that records transactional changes occurring in a database, providing a basis for updating a master file and establishing an audit trail." (Microsoft, "SQL Server 2012 Glossary", 2012)

"A collection of records that sequentially describes the events that occur in a system. A record of events." (Sybase, "Open Server Server-Library/C Reference Manual", 2019)

"A set of primary and secondary log files consisting of log records that record all changes to a database. The database log is used to roll back changes for units of work that are not committed and to recover a database to a consistent state." (Sybase, "Open Server Server-Library/C Reference Manual", 2019)

🛢DBMS: Entity Relationship Diagram [ERD] (Definitions)

"A graphical method of showing the entities, relationships, and attributes in a data model." (Owen Williams, "MCSE TestPrep: SQL Server 6.5 Design and Implementation", 1998)

"Drawings of boxes and lines to communicate the relationship between tables. Both third normal form (3NF) and dimensional models can be represented as ER diagrams because both consist of joined relational tables. The key difference between the models is the degree of dimension normalization. A dimensional model is a second normal form (2NF) model." (Ralph Kimball & Margy Ross, "The Data Warehouse Toolkit" 2nd Ed., 2002)

"The ERD is a proven and reliable data-modeling approach with straightforward rules of construction. The normalization rules yield a stable, consistent data model that upholds the policies and rules of engagement established by the enterprise. The resulting database schema is the most efficient in terms of storage and data loading as well." (Claudia Imhoff et al, "Mastering Data Warehouse Design", 2003)

"A diagram that represents the structural contents (the fields) in tables for an entire schema, in a database. Additionally included are schematic representations of relationships between entities, represented by various types of relationships, plus primary and foreign keys." (Gavin Powell, "Beginning Database Design", 2006)

"A diagram (or graph) of entities and their relationships, and possibly the attributes of those entities." (Toby J Teorey, ", Database Modeling and Design" 4th Ed., 2010)

"A diagram that depicts an entity relationship model’s entities, attributes, and relations." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management" 9th Ed, 2011)

"The graphical diagram for an Entity Relationship data model. The underlying data model generally includes more semantics than is or can be represented in the view shown on the diagram, e.g., some business rules." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

 "An E/R diagram graphically depicts the entities and relationships of a data model." (Craig S Mullins, "Database Administration: The Complete Guide to DBA Practices and Procedures" 2nd Ed, 2012)

🛢DBMS: Normalization (Definitions)

"Normalization is the database design process of discarding repeating groups, minimizing redundancy, eliminating composite keys for partial dependency, and separating non-key attributes. Various levels of normalization and various rules or tests have been formalized for performing normalization." (Microsoft Corporation, "Microsoft SQL Server 7.0 Data Warehouse Training Kit", 2000)

"The process of transforming database designs into logical structures by following rules and principles of relational database theory. Different 'normal forms' exist, each further reducing both redundancy and the possibility of update anomalies. 'Third normal form' is a design in which all the attributes of each row 'depend on the key, the whole key, and nothing but the key'." (Bill Pribyl & Steven Feuerstein, "Learning Oracle PL/SQL", 2001)

"The process of designing a database so that its tables follow the rules specified by relational theory. In practice, this usually means that all database tables are in third normal form." (Peter Gulutzan & Trudy Pelzer, "SQL Performance Tuning", 2002)

"Normalization is a method for ensuring that the data model meets the objectives of accuracy, consistency, simplicity, nonredundancy, and stability. It is a physical database design technique that applies mathematical rules to the relational data model to identify and reduce insertion, updating, or deletion anomalies." (Claudia Imhoff et al, "Mastering Data Warehouse Design", 2003)

"A formal approach in data modeling that examines and validates attributes and their entities in the Logical data model. The purpose of data normalization is to ensure that each attribute belongs to the entity to which it has been assigned, that redundant storage of information is minimized, and that storage anomalies are eliminated." (Sharon Allen & Evan Terry, "Beginning Relational Data Modeling 2nd Ed.", 2005)

"Developed by Dr. E. F. Codd in 1970, database normalization is the process of simplifying data and database design to achieve maximum performance and simplicity. This process involves the removing of useless and redundant data." (Thomas Moore, "EXAM CRAM™ 2: Designing and Implementing Databases with SQL Server 2000 Enterprise Edition", 2005)

"A process by which a relational schema design is adjusted to reduce the possibility of storing data redundantly. As a schema is normalized, attributes that contain repeating values are moved into new tables and replaced by a foreign key. This process requires analyzing and understanding the dependencies among attributes and key columns. There are several degrees of normalization, which formally describe the extent to which redundancies have been removed. Third normal form (3NF) is widely accepted as the optimal relational design for a transaction system. A star schema design is often referred to as denormalized, although it is actually in second normal form." (Christopher Adamson, "Mastering Data Warehouse Aggregates", 2006)

"The organization of data to reduce redundancy by creating many linked tables so that a value is stored in only one place." (Reed Jacobsen & Stacia Misner, "Microsoft SQL Server 2005 Analysis Services Step by Step", 2006)

"The process of simplifying the structure of data. Normalization increases granularity and Granularity is the scope of a definition for any particular thing. The more granular a data model is, the easier it becomes to manage, up to a point, depending, of course, on the application of the database model." (Gavin Powell, "Beginning Database Design", 2006)

"A formal process of removing redundancy from a database design by separating it into children tables from the parent table." (Victor Isakov et al, "MCITP Administrator: Microsoft SQL Server 2005 Optimization and Maintenance (70-444) Study Guide", 2007)

"Logical design process in which data is separated into multiple, related tables. The process allows databases to perform optimally." (Sara Morganand & Tobias Thernstrom , "MCITP Self-Paced Training Kit : Designing and Optimizing Data Access by Using Microsoft SQL Server 2005 - Exam 70-442", 2007)

"The design process for generating entity specifications to minimize both data redundancy and update anomalies." (S. Sumathi & S. Esakkirajan, "Fundamentals of Relational Database Management Systems", 2007)

"A series of database design recommendations that dictate how information should be dispersed among tables as well as how these tables should relate." (Robert D. Schneider and Darril Gibson, "Microsoft SQL Server 2008 All-In-One Desk Reference For Dummies", 2008)

"The process of transforming the database's structure to minimize the changes of certain kinds of data anomalies." (Rod Stephens, "Beginning Database Design Solutions", 2008)

"The process of designing relations to adhere to increasingly stringent sets of rules to avoid problems with poor database design." (Jan L Harrington, "Relational Database Design and Implementation" 3rd Ed., 2009)

"The process of breaking up a table into smaller tables to eliminate problems with unwanted loss of data (the egregious side effects of losing data integrity) from the deletion of records and inefficiencies associated with multiple data updates." (Toby J Teorey, ", Database Modeling and Design" 4th Ed., 2010)

"The process, originally articulated by Dr. E. F. Codd in his relational theory, for organizing data to reduce redundancy to the minimum possible. It involves guaranteeing that each attribute in a 'relation' (table or entity class) is truly an attribute of that relation and none other. The process involves organizing data to follow the constraints of at least first normal form, second normal form, and third normal form. Additional value is found in Boyce-Codd normal form, fourth normal form, and fifth normal form." (David C Hay, "Data Model Patterns: A Metadata Map", 2010)

"A process that assigns attributes to entities in such a way that data redundancies are reduced or eliminated." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management 9th Ed", 2011)

"The process of organizing data to minimize redundancy and remove ambiguity. In simple terms, normalization is the process of identifying the one best place each fact belongs." (Craig S Mullins, "Database Administration", 2012)

"The process of organizing data at its detailed level into according to its existence criteria" (Daniel Linstedt & W H Inmon, "Data Architecture: A Primer for the Data Scientist", 2014)

"The process of restructuring a data model by reducing its relations to their simplest forms. It is a key step in the task of building a logical relational database design. Normalization helps avoid redundancies and inconsistencies in data. An entity is normalized if it meets a set of constraints for a particular normal form (first normal form, second normal form, and so on)." (Sybase, "Open Server Server-Library/C Reference Manual", 2019)

🛢DBMS: Transactions (Definitions)

"A mechanism for ensuring that a set of actions is treated as a single unit of work." (Karen Paulsell et al, "Sybase SQL Server: Performance and Tuning Guide", 1996)

"A series of SQL statements that constitute an atomic unit of work: either all are committed as a unit or they are all rolled back as a unit. A transaction begins with the first statement since the last transaction end and finishes with a transaction end (either COMMIT or ROLLBACK) statement." (Peter Gulutzan & Trudy Pelzer, "SQL Performance Tuning", 2002)

"A group of database operations combined into a logical unit of work that is either wholly committed or rolled back. A transaction is atomic, consistent, isolated, and durable." (Anthony Sequeira & Brian Alderman, "The SQL Server 2000 Book", 2003)

"A logical unit of work consisting of one or more SQL statements that must all succeed or all fail to keep the database in a logically consistent state. A transfer of funds from a bank account is a logical transaction, in that both the withdrawal from one account and the deposit to another account must succeed for the transaction to succeed." (Bob Bryla, "Oracle Database Foundations", 2004)

"A series of database operations that should be treated as a single atomic operation so either they all occur or none of them occur." (Rod Stephens, "Beginning Database Design Solutions", 2008)

"One or more SQL statements that make up a unit of work performed against the database. Either all the statements in a transaction are committed as a unit or all the statements are rolled back as a unit." (John Goodson & Robert A Steward, "The Data Access Handbook", 2009)

"A group of database operations combined into a logical unit of work that is either wholly committed or rolled back. A transaction is atomic, consistent, isolated, and durable." (Jim Joseph, "Microsoft SQL Server 2008 Reporting Services Unleashed", 2009)

"An atomic unit of work with respect to recovery and consistency." (Craig S Mullins, "Database Administration: The Complete Guide to DBA Practices and Procedures" 2nd Ed, 2012)

"An atomic unit of work with respect to recovery and consistency." (Craig S Mullins, "Database Administration", 2012)

"Each individual purchase. Each time customers swipe a card, shell out cash, or press the purchase confirmation button online, a transaction takes place. This data often is referred to as transaction log (T-log) data." (Brittany Bullard, "Style and Statistics", 2016)

🛢DBMS: Entity-Relationship Model [ERM] (Definitions)

"A common way to organize, think about, or discuss the elements of the 'real world' that a database design will represent, by dividing them into entities and relationships." (Bill Pribyl & Steven Feuerstein, "Learning Oracle PL/SQL", 2001)

"A type of conceptual data model that represents structured data in terms of entities and relationships. An entity-relationship diagram can be used to represent information objects and their relationships visually. Because the constructs used in the entity-relationship model can easily be transformed into relational tables, this type of model is often used in database design." (J P Getty Trust, "Introduction to Metadata" 2nd Ed., 2008)

"A data model that is used to represent data in its purest form and to define relationships between different entities." (Laura Reeves, "A Manager's Guide to Data Warehousing", 2009)

"A technique for representing entity relationships that is independent of any specific data model and any specific software." (Jan L Harrington, "Relational Database Design and Implementation" 3rd Ed., 2009)

"A conceptual data model involving entities, relationships among entities, and attributes of those entities." (Toby J Teorey, ", Database Modeling and Design" 4th Ed., 2010)

"A data model developed by P. Chen in 1975. It describes relationships (1:1, 1:M, and M:N) among entities at the conceptual level with the help of ER diagrams." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management" 9th Ed., 2011)

"An abstract and conceptual representation of data. Entity-relationship model consists of a set of entities, characterized by attributes and linked by relationships." (International Qualifications Board for Business Analysis, "Standard glossary of terms used in Software Engineering", 2011)

"1.Generally, a record-based data modeling scheme that focuses on entities and relationships in the presentation of data model diagrams, thus suppressing the display of attributes. A true ER model allows multi-valued data items and repeating groups of items (nested relations, thus violating first normal form), retains M:N relationships, attributed relationships, subtypes/supertypes, ternary and higher-order relationships, none of which can be represented directly in a relational data model. A true ER model generally excludes (defers) the representation of entity identifiers and foreign keys. Originally proposed and named by Peter Chen (1976). 2.In relational modeling, the most popular style of data model, defining entities and the business relationships between the entities. Some more detailed models include also some of the attributes of these entities, usually those involved in the relationships as keys." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A data management approach that graphically represents relationships between data. This allows developers to create new relationships between data sources without complex programming." (Marcia Kaufman et al, "Big Data For Dummies", 2013)

"A logical view of data within a system, representing the entities in the system as well as relationships among the entities, attributes of the entities, and attributes of the relationships." (IEEE 610.5-1990)

🛢DBMS: Pass-Through Query (Definitions)

"A query that is passed uninterpreted to an external server for evaluation. The result set returned by a pass-through query can be used in the FROM clause of a query like an ordinary base table." (Microsoft Corporation, "SQL Server 7.0 System Administration Training Kit", 1999)

"A query that is passed through uninterrupted to an external database engine." (Marilyn Miller-White et al, "MCITP Administrator: Microsoft® SQL Server™ 2005 Optimization and Maintenance 70-444", 2007)

"An SQL-specific query you use to send commands directly to an ODBC database server." (Microsoft, "SQL Server 2012 Glossary", 2012)

🛢DBMS: Record (Definitions)

"A group of related fields (columns) of information treated as a unit. A record is more commonly called a row in a SQL database." (Microsoft Corporation, "SQL Server 7.0 System Administration Training Kit", 1999)

"A row in a database table." (Bill Pribyl & Steven Feuerstein, "Learning Oracle PL/SQL", 2001)

"An aggregation of values of data organized by their relation to a common key." (William H Inmon, "Building the Data Warehouse", 2005)

"In relational databases, a single instance in a table. In the context of hierarchical and network databases, a record is a data structure." (Sharon Allen & Evan Terry, "Beginning Relational Data Modeling" 2nd Ed., 2005)

"A repetition of a field structure across a table. Records repeat field structure in a table, where each repeated field can (and sometimes should) have a different value. Tables are divided into fields and records. Fields impose structure and datatype specifics onto each of the field values, in each record." (Gavin Powell, "Beginning Database Design", 2006)

"This is a group of related fields containing information about a single entity." (Joseph L Jorden & Dandy Weyn, "MCTS Microsoft SQL Server 2005: Implementation and Maintenance Study Guide - Exam 70-431", 2006)

"A grouping of information typically returned from a query or other database operation. It can consist of data from only one table or be an aggregation of information dispersed among many tables" (Robert D Schneider and Darril Gibson, "Microsoft SQL Server 2008 All-In-One Desk Reference For Dummies", 2008)

"In a file processing system, a collection of data that describes one instance of an entity." (Jan L Harrington, "Relational Database Design and Implementation" 3rd Ed., 2009)

"A group of data items treated as a unit by an application; a row in a database table." (Toby J Teorey, ", Database Modeling and Design" 4th Ed., 2010)

"A collection of related (logically connected) fields." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management 9th Ed", 2011)

"Related characters combined into a field or related fields, such as vendor name, address, and account data." (Linda Volonino & Efraim Turban, "Information Technology for Management 8th Ed", 2011)

"A set of related data values in a file or stream, often associated with a unique key field." (Jon Orwant et al, "Programming Perl" 4th Ed., 2012)

"The physical representation of data about an instance in a flat file." (Craig S Mullins, "Database Administration: The Complete Guide to DBA Practices and Procedures 2nd Ed", 2012)

"A unit of data that typically contains keys and attributes" (Daniel Linstedt & W H Inmon, "Data Architecture: A Primer for the Data Scientist", 2014)

"A collection of related data items." (Adam Gordon, "Official (ISC)2 Guide to the CISSP CBK" 4th Ed., 2015)

"A collection of related fields in a table. In Excel, each record goes into a separate row." (E C Nelson & Stephen L Nelson, "Excel Data Analysis For Dummies ", 2015)

"A row in a table, storing information about a specific person, place, or thing." (Faithe Wempen, "Computing Fundamentals: Introduction to Computers", 2015)

"In a relational database, a single set of values in a table. For example, a particular student’s data would be contained in a record in the Students table. Also called rows or tuples." (Rod Stephens, "Beginning Software Engineering", 2015)

"A collection of related fields that make up a single database entry" (Nell Dale & John Lewis, "Computer Science Illuminated" 6th Ed., 2015)

🛢DBMS: Row (Definitions)

"A set of related columns that describes a specific entity. Also called record." (Karen Paulsell et al, "Sybase SQL Server: Performance and Tuning Guide", 1996)

"A data structure that is a collection of elements (columns), each with its own name and type. A row can be accessed as a collective unit of elements, or the elements can be accessed individually. A row is equivalent to a record." (Microsoft Corporation, "SQL Server 7.0 System Administration Training Kit", 1999)

"In a relational database table, a primary key value plus the associated values of each non-key column. The number of rows usually varies over time." (Bill Pribyl & Steven Feuerstein, "Learning Oracle PL/SQL", 2001)

"A record in a relational table." (Ralph Kimball & Margy Ross, "The Data Warehouse Toolkit 2nd Ed ", 2002)

"The collection of elements that form a horizontal line in the table. Each row in the table represents a single occurrence of the object modeled by the table and stores the values for all the attributes of that object." (Anthony Sequeira & Brian Alderman, "The SQL Server 2000 Book", 2003)

"A group of one or more data elements in a database table that describes a person, place, or thing." (Bob Bryla, "Oracle Database Foundations", 2004)

"A single instance in a table. This is also called a record." (Sharon Allen & Evan Terry, "Beginning Relational Data Modeling" 2nd Ed., 2005)

"A group of related column values in a table. The corresponding formal database term is tuple." (Rod Stephens, "Beginning Database Design Solutions", 2008)

"An individual entry from a given table. For example, a table may contain details about thousands of customers; a specific customer’s data will be found in one row. See also record." (Robert D Schneider & Darril Gibson, "Microsoft SQL Server 2008 All-in-One Desk Reference For Dummies", 2008)

"A horizontal line in the table that contains all attributes of a single object modeled in the table." (Jim Joseph, "Microsoft SQL Server 2008 Reporting Services Unleashed", 2009)

"In relational theory, a set of values for a specified set of attributes." (David C Hay, "Data Model Patterns: A Metadata Map", 2010)

"A group of data items treated as a unit by an application; a record; a tuple in relational database terminology." (Toby J Teorey, ", Database Modeling and Design" 4th Ed., 2010)

"A set of column values describing one logical instance in a relational database table. Technically called a tuple in relational calculus. Equivalent to a record in a flat file." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A set of column values describing one logical instance in a table." (Craig S Mullins, "Database Administration", 2012)

"The horizontal component of a table, consisting of a sequence of values, one for each column of the table." (Sybase, "Open Server Server-Library/C Reference Manual", 2019)

🛢DBMS: One-to-Many Relationship (Definitions)

"An instance of an entity is associated with zero or several instances of another entity." (Owen Williams, "MCSE TestPrep: SQL Server 6.5 Design and Implementation", 1998)

"A relationship between two tables in which a single row in the first table can be related to one or more rows in the second table, but a row in the second table can be related only to one row in the first table. A typical one-to-many relationship is between the publishers table and the titles table in the pubs sample database, in which each publisher can be related to several titles, but each title can be related to only one publisher." (Microsoft Corporation, "SQL Server 7.0 System Administration Training Kit", 1999)

"A logical data relationship in which the value of one data element can exist in combination with many values of another data element, but not vice versa." (Ralph Kimball & Margy Ross, "The Data Warehouse Toolkit" 2nd Ed., 2002)

"A relationship type between tables where one row in a given table is related to many other rows in a child table. The reverse condition, however, is not true. A given row in a child table is related to only one row in the parent table." (Bob Bryla, "Oracle Database Foundations", 2004)

"These relationships exist when a single instance of an entity (the parent entity) relates to many instances of another entity (the child entity). One-to-many relationships are the most common relationships in the real world." (Thomas Moore, "EXAM CRAM™ 2: Designing and Implementing Databases with SQL Server 2000 Enterprise Edition", 2005)

"The relationship between two tables dictated by having one record in one table, and many related records in another table." (Gavin Powell, "Beginning Database Design", 2006)

"The use of one key value from a dimension table in many rows of a fact table." (Reed Jacobsen & Stacia Misner, "Microsoft SQL Server 2005 Analysis Services Step by Step", 2006)

"A relationship between two tables in which a single row in the first table can be related to one or more rows in the second table, but a row in the second table can be related only to one row in the first table." (S. Sumathi & S. Esakkirajan, "Fundamentals of Relational Database Management Systems", 2007)

"Used in a relational database to denote that a single row in the parent table can be related to one or more rows in the related child table but that a row in the child table can be related to only a single row in the referenced parent table." (Marilyn Miller-White et al, "MCITP Administrator: Microsoft SQL Server 2005 Optimization and Maintenance 70-444", 2007)

"A relationship where one object of one type may correspond to many objects of another type. For example, one INSTRUCTOR may teach many COURSEs but each COURSE has only one INSTRUCTOR." (Rod Stephens, "Beginning Database Design Solutions", 2008)

"One of three types of relationships (associations among two or more entities) that are used by data models. In a 1:M relationship, one entity instance is associated with many instances of the related entity." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management" 9th Ed., 2011)

"A link between two entities in which the cardinality of one side of the relationship is one and the other is multiple." (Craig S Mullins, "Database Administration", 2012)

"A relationship in which the connected field is unique in one table and not unique in the other table." (Faithe Wempen, "Computing Fundamentals: Introduction to Computers", 2015)

"A relationship between two entities in a database such that one instance of an entity can be related to many instances of a second entity and the second entity can be related to only one instance of the first." (Jan L Harrington, "Relational Database Design and Implementation" 3rd Ed., 2009)

🛢DBMS: Domain Integrity (Definitions)

"Describes the inclusion of attribute rules (for example, maximum discount and minimum order quantity) within the design of a database." (Owen Williams, "MCSE TestPrep: SQL Server 6.5 Design and Implementation", 1998)

"Integrity that enforces valid entries for a given column. Domain integrity is enforced by restricting the type (through data types), the format (through CHECK constraints and rules), or the range of possible values (through REFERENCE and CHECK constraints, and rules)." (Microsoft Corporation, "SQL Server 7.0 System Administration Training Kit", 1999)

"Domain integrity enforces the validity of entries for a given column. The mechanism, such as the CHECK constraint, can restrict the possible data values by data type, format, or range of values allowed." (Anthony Sequeira & Brian Alderman, "The SQL Server 2000 Book", 2003)

"A relational database integrity mechanism that enforces the validity of data at the column level." (Marilyn Miller-White et al, "MCITP Administrator: Microsoft® SQL Server™ 2005 Optimization and Maintenance 70-444", 2007)

"The validity of entries for a specific column of data." (Microsoft, "SQL Server 2012 Glossary", 2012)

🛢DBMS: Subquery (Definitions)

"A SELECT statement nested inside another SELECT, INSERT, UPDATE, or DELETE statement, or inside another subquery." (Patrick Dalton, "Microsoft SQL Server Black Book", 1997)

"A SELECT statement that is usually a part of a larger SQL statement; a query nested inside a SELECT, INSERT, UPDATE, or DELETE statement." (Owen Williams, "MCSE TestPrep: SQL Server 6.5 Design and Implementation", 1998)

"A SELECT within another SQL statement, usually within another SELECT." (Peter Gulutzan & Trudy Pelzer, "SQL Performance Tuning", 2002)

"A query that is embedded in a main, or parent, query and used to assist in filtering the result set from a query." (Bob Bryla, "Oracle Database Foundations", 2004)

"A nested query that returns information to an outer query, thereby helping the outer query correctly identify results." (Robert D. Schneider and Darril Gibson, "Microsoft SQL Server 2008 All-In-One Desk Reference For Dummies", 2008)

"A complete SELECT statement that is part of another SELECT." (Jan L Harrington, "SQL Clearly Explained 3rd Ed. ", 2010)

"A SELECT statement that contains one or more subqueries." (SQL Server 2012 Glossary, "Microsoft", 2012)

"A query nested within another SQL statement. Unlike implicit queries, subqueries use a SELECT statement to retrieve data." (Oracle, "Database SQL Tuning Guide Glossary", 2013)

"A form of a full-select that is enclosed within parentheses and used as a component of a query." (Sybase, "Open Server Server-Library/C Reference Manual", 2019)

🛢DBMS: Conceptual Data Model (Definitions)

"Represents the overall logical structure of a database, which is independent of any software or data storage structure. A Conceptual model often contains data objects not yet implemented in the physical databases. It gives a formal representation of the data needed to run an enterprise or a business activity." (Sharon Allen & Evan Terry, "Beginning Relational Data Modeling" 2nd Ed., 2005)

"An organization of data that describes the relationships among the primitive data elements. For example, in the ER model, it is a diagram of the entities, their relationships, and their attributes." (Sam Lightstone et al, "Physical Database Design: The Database Professional’s Guide to Exploiting Indexes, Views, Storage, and More", 2007)

"An abstract model or representation of data for a particular domain, business enterprise, field of study, etc., independent of any specific software or information system. Usually expressed in terms of entities and relationships." (J P Getty Trust, "Introduction to Metadata" 2nd Ed., 2008)

"An organization of data that describes the relationships among the primitive data elements. For example, in the ER model, it is a diagram of the entities, their relationships, and their attributes." (Toby J Teorey, ", Database Modeling and Design" 4th Ed, 2010)

"In the ANSI four-schema architecture, this is a description of a portion of an enterprise in terms of the fundamental things of significant interest to it. They are fundamental in that most things seen by business owners are examples of these. The model is constructed in a rigorous manner, being fully normalized, eschewing many-to-many relationships and is expressed in terms of binary relationships only." (David C Hay, "Data Model Patterns: A Metadata Map", 2010)

"A data model that is presented at a high level of abstraction, hiding the underlying details, and making it easier for people to comprehend. A conceptual model should reflect the phenomena in the users' world being modeled as directly as possible, as close to the way the users think. For example, many-to-many relationships are common in conceptual models." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A high-level data model identifying major entities and relationships, not fully attributed and therefore not necessarily normalized." (Craig S Mullins, "Database Administration: The Complete Guide to DBA Practices and Procedures" 2nd Ed., 2012)

"A high-level data modeling that specifies an abstract map of concepts and their relationships. SQL’s inherent hierarchical data modeling does this easily and naturally." (Michael M David & Lee Fesperman, "Advanced SQL Dynamic Data Modeling and Hierarchical Processing", 2013)

"A detailed model that captures the overall structure of organizational data that is independent of any database management system or other implementation considerations." (Jeffrey A. Hoffer et al, "Modern Systems Analysis and Design" 7th Ed., 2014)

"The output of the conceptual design process. The conceptual model provides a global view of an entire database. Describes the main data objects, avoiding details." (Carlos Coronel & Steven Morris, "Database Systems: Design, Implementation, & Management"  Ed. 11, 2014)

"A model of a database expressed at platform independent level; describes entities from a considered domain, properties of these entities, and the relationships between entities." (Iwona Dubielewicz et al, "Quality-Driven Database System Development within MDA Approach", 2015)

"The most abstract form of data model. It includes the important entities and the relationships among them and contains only major attributes." (Besma Khalfi et al, "Enhanced F-Perceptory Approach for Dealing with Geographic Data Imprecision from the Conceptual Modeling to the Fuzzy Geographical Database Building", 2017)