🛢DBMS: Data Integrity (Definitions)

"The correctness and completeness of data within a database." (Karen Paulsell et al, "Sybase SQL Server: Performance and Tuning Guide", 1996)

"A general term that refers to the correctness of the data contained in a database." (Owen Williams, "MCSE TestPrep: SQL Server 6.5 Design and Implementation", 1998)

"The accuracy and reliability of data. Data integrity is important in both single-user and multiuser environments. In multiuser environments, where data is shared, both the potential for and the cost of data corruption are high. In large-scale relational database management system (RDBMS) environments, data integrity is a primary concern." (Microsoft Corporation, "SQL Server 7.0 System Administration Training Kit", 1999)

"Data integrity refers to a state in which all the data values stored in the database are correct." (Anthony Sequeira & Brian Alderman, "The SQL Server 2000 Book", 2003)

"The condition that exists when there’s no accidental or intentional destruction, alteration, or loss of data." (Sharon Allen & Evan Terry, "Beginning Relational Data Modeling" 2nd Ed., 2005)

"The bits of data that are put in storage (via I/O writes) are the same bits of data—order and completeness - that come out (via I/O reads)." (David G Hill, "Data Protection: Governance, Risk Management, and Compliance", 2009)

"In a relational database, refers to a condition in which the data in the database is in compliance with all entity and referential integrity constraints." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management 9th Ed", 2011)

"The accuracy of data and its conformity to its expected value, especially after being transmitted or processed." (Microsoft, "SQL Server 2012 Glossary", 2012)

"Refers to the accuracy and quality of the data." (Steve Conger, "Hands-on database : an introduction to database design and development", 2012)

"Data integrity is the state of data being free from corruption." (Vince Buffalo, "Bioinformatics Data Skills", 2015)

"The property that data has not been altered in an authorized manner." (O Sami Saydjari, "Engineering Trustworthy Systems: Get Cybersecurity Design Right the First Time", 2018)

"The degree to which the data is internal or referential/consistent. If the key to refer to a different table is invalid, the join between the two tables cannot be made." (Piethein Strengholt, "Data Management at Scale", 2020)

"(1) In the context of data and network security: The assurance that information can only be accessed or modified by those authorized to do so. (2) In the context of data quality: The assurance the data are clean, traceable, and fit for purpose." (CODATA)

"The degree to which a collection of data is complete, consistent, and accurate. See also: data security; database integrity; integrity." (IEEE 610.5-1990)

🛢DBMS: Atomic(-level) Data (Definitions)

"Data elements that represent the lowest level of granularity. Depending on the context, this term may refer all the way back to the transactions from the operational systems, or it may refer to the base granularity held in a data warehouse." (Microsoft Corporation, "Microsoft SQL Server 7.0 Data Warehouse Training Kit", 2000)

"The most detailed granular data captured by a business process. Atomic data must be made available in the data presentation area to respond to unpredictable ad hoc queries." (Ralph Kimball & Margy Ross, "The Data Warehouse Toolkit 2nd Ed ", 2002)

"Data elements that represent the lowest level of detail. For example, in a daily sales report, the individual items sold would be atomic data, and roll-ups such as invoice and summary totals from invoices are aggregate data." (Sharon Allen & Evan Terry, "Beginning Relational Data Modeling 2nd Ed.", 2005)

"Data with the lowest level of granularity. Atomic-level data sits in a data warehouse and is time-variant (that is, accurate as of some moment in time now passed)." (William H Inmon, "Building the Data Warehouse", 2005)

"1.Data at the lowest chosen level of detail (granularity). The level of detail chosen depends on the information requirements of the enterprise. For example, address could be one atomic item, or address could be split into further composite items such as house identifier and city. Opposite of aggregate data. 2.Non-aggregated observations, or measurements of characteristics of individual units, which cannot be further decomposed and retain any useful meaning." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"Data at the lowest available level of detail or granularity." (Craig S Mullins, "Database Administration", 2012)

🛢DBMS: Column (Definitions)

"The logical equivalent of a field. A column contains an individual data item within a row or record." (Karen Paulsell et al, "Sybase SQL Server: Performance and Tuning Guide", 1996)

"In a SQL database table, the area, sometimes called a field, in each row that stores the data about an attribute of the object modeled by the table (for example, the ContactName column in the Customers table of the Northwind database). Individual columns are characterized by their maximum length and the type of data that can be placed in them. A column contains an individual data item within a row." (Microsoft Corporation, "SQL Server 7.0 System Administration Training Kit", 1999)

"A named portion of a table that can hold some number of data values of a particular datatype. Columns usually have some maximum width or number of bytes. The names and datatypes of a table's columns typically do not vary over time." (Bill Pribyl & Steven Feuerstein, "Learning Oracle PL/SQL", 2001)

"The area in each row that stores the data value for some attribute of the object modeled by the table." (Anthony Sequeira & Brian Alderman, "The SQL Server 2000 Book", 2003)

"The component of a database table that contains all of the data of the same name and type across all rows." (Bob Bryla, "Oracle Database Foundations", 2004)

"A piece of data that may be recorded for each row in a table. The corresponding formal database term is attribute." (Rod Stephens, "Beginning Database Design Solutions", 2008)

"Stored within tables, a column contains a particular piece of information." (Robert D Schneider & Darril Gibson, "Microsoft SQL Server 2008 All-in-One Desk Reference For Dummies", 2008)

"In a table, the area in each row that stores the data value for some attribute of the object presented in the table. For example, in an Employee table, a FirstName column would contain the first name of an employee." (Jim Joseph, "Microsoft SQL Server 2008 Reporting Services Unleashed", 2009)

"A data attribute as implemented in a relational database as a vertical component of a table, similar to a field in a flat file record." (Craig S Mullins, "Database Administration", 2012)

"The area in each row of a database table that stores the data value for some attribute of the object modeled by the table." (Microsoft, "SQL Server 2012 Glossary", 2012)

"A column is the data structure for storing a single value in a column family database." (Dan Sullivan, "NoSQL for Mere Mortals", 2015)

"The vertical component of a database table. A column has a name and a particular data type (for example, character, decimal, or integer)." (Sybase, "Open Server Server-Library/C Reference Manual", 2019)

🛢DBMS: Flat File (Definitions)

"A simple data structure, often implemented on a mainframe, that relies on nonrelational files, such as IBM VSAM files." (Ralph Kimball & Margy Ross, "The Data Warehouse Toolkit 2nd Ed ", 2002)

"A collection of records containing no data aggregates, nested repeated data items, or groups of data items." (William H Inmon, "Building the Data Warehouse", 2005)

"A collection of records that are related to one another that haven’t been organized to meet relational normal forms. Originally a file was stored only outside a database. Now you can refer to a table structured this way as a flat file." (Sharon Allen & Evan Terry, "Beginning Relational Data Modeling" 2nd Ed., 2005)

"A data structure that contains records with no inherent relationships." (Evan Levy & Jill Dyché, "Customer Data Integration", 2006)

"A term generally applying to an unstructured file, such as a text file." (Gavin Powell, "Beginning Database Design", 2006)

"A file in which the fields of records are simple atomic values." (S. Sumathi & S. Esakkirajan, "Fundamentals of Relational Database Management Systems", 2007)

"A plain old text file used to store data. A flat file isn't very fancy and provides few tools for querying, sorting, grouping, and performing other database operations but flat files are very easy to use." (Rod Stephens, "Beginning Database Design Solutions", 2008)

"A file in which all the attribute fields are atomic, that is, single valued." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A file consisting of records of a single record type in which there is no embedded structure information that governs relationships between records." (Microsoft, "SQL Server 2012 Glossary", 2012)

"Plain text file wherein each line of the file holds one record, typically with fields separated by delimiters, such as commas or tabs." (Craig S Mullins, "Database Administration", 2012)

"A collection of records where the structure of each record is identical" (Daniel Linstedt & W H Inmon, "Data Architecture: A Primer for the Data Scientist", 2014)

🛢SQL Server: Parameterization (Definitions)

"Parameterization is the act of using named or positional markers in place of constant values in a T-SQL query or statement. The actual values are passed to SQL Server independently of the actual query." (Michael Coles, "Pro T-SQL 2008 Programmer's Guide", 2008)

"The act of using parameters or parameter markers rather than constant values." (Jim Joseph, "Microsoft SQL Server 2008 Reporting Services Unleashed", 2009)

"Parameterization is the act of using named or positional markers in place of constant values in a T-SQL query or statement. The actual values are passed to SQL Server independently of the actual query." (Jay Natarajan et al, "Pro T-SQL 2012 Programmer's Guide" 3rd Ed., 2012)

"The act of using named or positional markers in place of constant values in a T-SQL query or statement. The actual values are passed to SQL Server independently of the actual query." (Miguel Cebollero et al, "Pro T-SQL Programmer’s Guide" 4th Ed., 2015)

🛢DBMS: Data Model (Definitions)

"A method of organizing data into two-dimensional tables made up of rows and columns. The model is based on the mathematical theory of relations, a part of set theory." (Microsoft Corporation, "SQL Server 7.0 System Administration Training Kit", 1999)

"A representation, usually graphical, of objects and their relationships, generally undertaken as part of designing an Oracle database application." (Bill Pribyl & Steven Feuerstein, "Learning Oracle PL/SQL", 2001)

"A formal way of describing the relationship between entities in a database to a database management system." (Jan L Harrington, "Relational Database Dessign: Clearly Explained" 2nd Ed., 2002)

"A data model is an abstraction or representation of the data in a given environment. It is a collection and subsequent verification and communication method for fully documenting the data requirements used in the creation of accurate, effective, and efficient physical databases. The data model consists of entities, attributes, and relationships." (Claudia Imhoff et al, "Mastering Data Warehouse Design", 2003)

"A data model is a schematic showing the data in the warehouse, how the data relate to other data, and how the data should be structured. It is used to ensure that the data warehouse can substantiate all business requirements." (Margaret Y Chu, "Blissful Data", 2004)

"An integrated collection of concepts for describing data, relationships between data, and constraints on the data used by an organization." (Thomas M Connolly & Carolyn E Begg, "Database Solutions: A step-by-step guide to building databases", 2004)

"The specification of data structures and business rules needed to support a defined set of functions (sometimes called an Information Model); usually depicted in a diagram consisting of entities and relationships." (Margaret Y Chu, "Blissful Data ", 2004)

"(1) A data model is an abstract, self-contained, logical definition of the data structures, data operators, and so forth, that together make up the abstract machine with which users interact. (2) A data model is a model of the persistent data of some particular enterprise." (Christopher J Date, "Database in Depth", 2005)

"A data model is the specification of data structures and business rules to represent business requirements. This is an abstraction that describes one or more aspects of a problem or a potential solution addressing a problem." (Sharon Allen & Evan Terry, "Beginning Relational Data Modeling" 2nd Ed., 2005)

"A model that provides a two-dimensional structure to data." (Gavin Powell, "Beginning Database Design", 2006)

[object database model:] "A model that provides a three-dimensional structure to data where any item in a database can be retrieved from any point very rapidly." (Gavin Powell, "Beginning Database Design", 2006)

"(1) The logical data structures, including operations and constraints provided by a DBMS for effective database processing; (2) the system used for the representation of data (for example, the ERD or relational model). " (William H Inmon & Anthony Nesavich, "Tapping into Unstructured Data", 2007)

"A formal description of data managed by a business process. In most cases, these data are stored via a Database Management System (DBMS), and are also referenced by an Information System (IS) and, possibly, by a Decision Support Systems (DSS)" (C Combi & G Pozzi, "Workflow Management Systems for Healthcare Processes", 2008)

[Entity Data Model] "An EDM is an abstract logical representation of a physical database, used to implement database connectivity in the middle or client tiers." (Michael Coles, "Pro T-SQL 2008 Programmer's Guide", 2008)

[navigational data model:] "A data model where relationships between entities are represented by physical data structures (for example, pointers or indexes) that provide the only paths for data access." (Jan L Harrington, "Relational Database Design and Implementation" 3rd Ed., 2009)

"A formal description language to describe and to manipulate the investigated data instances. It contains three components: a static structural part, an integrity part and a manipulation part." (László Kovács & Tanja Sieber, "Multi-Layered Semantic Data Models" [in "Encyclopedia of Artificial Intelligence"], 2009)

"A paradigm for describing the structure of a database in which entities are represented as tables, and relationships between the entities are represented by matching data." (Jan L Harrington, "Relational Database Design and Implementation" 3rd Ed., 2009)

"An abstraction of how individual data elements relate to each other. It visually depicts how the data is to be organized and stored in a database. A data model provides the mechanism to document and understand how data is organized. (Laura Reeves, "A Manager's Guide to Data Warehousing", 2009)

"The formal way of expressing relationships in a database." (Jan L Harrington, "Relational Database Design and Implementation" 3rd Ed., 2009)

"A representation of the structure of data. As used in this book, the term refers to a conceptual data model, which describes data in terms of their inherent semantics, without regard to how they might be organized in a physical database. Some use the term to describe a logical data model that organizes data in terms of a specific data management technology, such as relational tables and columns, object-oriented classes, or ISAM hierarchies." (David C Hay, "Data Model Patterns: A Metadata Map", 2010)

"A model that includes formal data names, comprehensive data definitions, proper data structures, and precise data integrity rules. A complete data model must include all four of these components." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A representation, usually graphic, of a complex 'real-world' data structure. Data models are used in the database design phase of the database life cycle." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management 9th Ed", 2011)

"A data model is a visual representation of data content and the relationships, created for purposes of understanding how data is or might be organized, and for ensuring the comprehensibility and usability of that way of organizing data." (Laura Sebastian-Coleman, "Measuring Data Quality for Ongoing Improvement ", 2012)

"A representation, usually graphic, of a complex 'real-world' data structure. Data models are used in the database design phase of the database life cycle." (Carlos Coronel & Steven Morris, "Database Systems: Design, Implementation, & Management" 11th Ed., 2014)

[Entity Data Model (EDM):] "An abstract logical representation of a physical database, used to implement database connectivity in the middle or client tiers." (Miguel Cebollero et al, "Pro T-SQL Programmer’s Guide 4th Ed", 2015)

"Represents data objects and their relationships with each other. Data models form the basis for data integration at the conceptual level as well as the improvement of data quality, such as with regard to the reduction of data redundancy.  Data models are one component of the data architecture." (Boris Otto & Hubert Österle, "Corporate Data Quality", 2015)

"A visual means of depicting data and its relationship to other data." (Gregory Lampshire, "The Data and Analytics Playbook", 2016)

"A description of the objects represented by a computer system together with their properties and relationships." (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)

"1. A representation, using text and/or graphics, of the definition, characterization, and relationships of data in a given environment. 2. No longer used, the DBMS architecture (hierarchical, network, relational, etc.)." (George Tillmann, "Usage-Driven Database Design: From Logical Data Modeling through Physical Schmea Definition", 2017)

"In a data-centric benchmark, a database schema and a protocol for instantiating this schema, i.e. , generating synthetic data or reusing real-life data." (Jérôme Darmont, "Data-Centric Benchmarking", Encyclopedia of Information Science and Technology, Fourth Edition, 2018)

"An abstract model that describes how data is presented and used." (Piethein Strengholt, "Data Management at Scale", 2020)

"A description of data that consists of all entities represented in a data structure or database and the relationships that exist among them." (IEEE 610.5-1990)

🛢DBMS: Constraints (Definitions)

"A restriction placed upon the value that can be entered into a column or a row. Values can be equal to, greater than, or less than. A constraint limits the input." (Patrick Dalton, "Microsoft SQL Server Black Book", 1997)

"A property assigned to a table column that prevents certain types of non-valid data values from being placed in the column." (Anthony Sequeira & Brian Alderman, "The SQL Server 2000 Book", 2003)

"A condition defined against a column or columns on a table in the database to enforce business rules or relationships between tables in the database." (Bob Bryla, "Oracle Database Foundations", 2004)

"A database object that can be applied to tables to enforce different types of data integrity." (Sara Morganand & Tobias Thernstrom , "MCITP Self-Paced Training Kit : Designing and Optimizing Data Access by Using Microsoft SQL Server 2005 - Exam 70-442", 2007)

"(1) A restriction on a business action and the resulting data. (2) The database mechanism for enforcing such." (Craig S Mullins, "Database Administration: The Complete Guide to DBA Practices and Procedures 2nd Ed", 2012)

"A rule that limits the values that can be inserted, deleted, or updated in a table." (Sybase)

🛢DBMS: Data Source (Definitions)

"The source of data for an object such as a cube or a dimension. Also, the specification of the information necessary to access source data. Sometimes refers to a DataSource object." (Microsoft Corporation, "SQL Server 7.0 System Administration Training Kit", 1999)

"A repository for storing data. An ODBC/JDBC term." (Peter Gulutzan & Trudy Pelzer, "SQL Performance Tuning", 2002)

"A file that contains the connection string that Analysis Services uses to connect to the database that hosts the data as well as any necessary authentication credentials." (Reed Jacobsen & Stacia Misner, "Microsoft SQL Server 2005 Analysis Services Step by Step", 2006)

"A system or application that generates data for use by another system or by an end user. The data source may also be the system of origin for the data." (Evan Levy & Jill Dyché, "Customer Data Integration", 2006)

"An information store that can be connected to by various SQL Server technologies such as SQL Server Reporting Services for data retrieval." (Marilyn Miller-White et al, "MCITP Administrator: Microsoft® SQL Server™ 2005 Optimization and Maintenance 70-444", 2007)

"An entity or group of entities from which data can be collected. The entities may be people, objects, or processes." (Jens Mende, "Data Flow Diagram Use to Plan Empirical Research Projects", 2009)

"An object containing information about the location of data. The data source leverages a connection string." (Jim Joseph et al, "Microsoft® SQL Server™ 2008 Reporting Services Unleashed", 2009)

"A repository of data to which a federated server can connect and then retrieve data by using wrappers. A data source can contain relational databases, XML files, Excel spreadsheets, table-structured files, or other objects. In a federated system, data sources seem to be a single collective database." (Sybase, "Open Server Server-Library/C Reference Manual", 2019)

🛢DBMS: Scalar Aggregate (Definitions)

"An aggregate function that produces a single value from a select statement that does not include a group by clause. This is true whether the aggregate function is operating on all the rows in a table or on a subset of rows defined by a where clause." (Karen Paulsell et al, "Sybase SQL Server: Performance and Tuning Guide", 1996)

[vector aggregate:] "A value that results from using an aggregate function with a group by clause." (Karen Paulsell et al, "Sybase SQL Server: Performance and Tuning Guide", 1996)

"When aggregate functions are applied to the whole or partial table without the GROUP BY clause and return only one row." (Owen Williams, "MCSE TestPrep: SQL Server 6.5 Design and Implementation", 1998)

[vector aggregates:] "When aggregate functions are used with the GROUP BY clause, they return values for each group. These are called vector aggregates." (Owen Williams, "MCSE TestPrep: SQL Server 6.5 Design and Implementation", 1998)

"A function applied to all of the rows in a table (producing a single value per function). An aggregate function in the select list with no GROUP BY clause applies to the whole table and is an example of a scalar." (Microsoft Corporation, "SQL Server 7.0 System Administration Training Kit", 1999)

[vector aggregate:] "Functions applied to all rows that have the same value in a specified column or expression by using the GROUP BY clause and, optionally, the HAVING clause (producing a value for each group per function)." (Microsoft Corporation, "SQL Server 7.0 System Administration Training Kit", 1999)

"An aggregate value that is calculated on the data source. Depending on the data source, server aggregates can be treated as detail data or as aggregates based on the dataset option InterpretSubtotalsAsDetails." (Microsoft Technet)

[aggregate of aggregates:] "A summary value calculated from aggregates, such as the maximum of a set of sums." (Microsoft Technet)

 "An aggregate function, such as MIN(), MAX(), or AVG(), that is specified in a SELECT statement column list that contains only aggregate functions." (Microsoft Technet)

🛢DBMS: Data Independence (Definitions)

[logical *:] "Application programs and terminal activities remain logically unimpaired when information preserving changes of any kind that theoretically permit unimpairment are made to the base tables." (S. Sumathi & S. Esakkirajan, "Fundamentals of Relational Database Management Systems", 2007)

[physical *]"Application programs and terminal activities remain logically unimpaired whenever any changes are made in either storage representation or access methods." (S. Sumathi & S. Esakkirajan, "Fundamentals of Relational Database Management Systems", 2007)

"A condition that exists when data access is unaffected by changes in the physical data storage characteristics." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management 9th Ed", 2011)

"Data independence is the characteristic that enables data to be easily combined into usually unlimited number of different structures." (Michael M David & Lee Fesperman, "Advanced SQL Dynamic Data Modeling and Hierarchical Processing", 2013)

"A condition that exists when data access is unaffected by changes in the physical data storage characteristics." (Carlos Coronel & Steven Morris, "Database Systems: Design, Implementation, & Management"  11th Ed., 2014)

"The isolation of data from the use of the data such that a change to one does not affect the other." (George Tillmann, "Usage-Driven Database Design: From Logical Data Modeling through Physical Schmea Definition", 2017)

"Data independence is a database management system (DBMS) characteristic that lets programmers modify information definitions and organization without affecting the programs or applications that use it. Such property allows various users to access and process the same data for different purposes, regardless of changes made to it." (Techslang) [source]

"The property of being able to change the overall logical or physical structure of the data without changing the application program's view of the data." (GRC Data Intelligence)

"The degree to which the logical view of a database is immune to changes in the physical structure of the database." (IEEE 610.5-1990)

🛢DBMS: Aggregate Data (Definitions)

"A group such as grouped data. For example, when aggregating data, we are grouping data. A common aggregate function is Avg (average). It looks at a group of data (an aggregate) and provides an average." (Darril Gibson, "MCITP SQL Server 2005 Database Developer All-in-One Exam Guide", 2008)

"Data resulting from processes that combine and summarize atomic data." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

[aggregate:] "Pertaining to a combination of multiple values." (Microsoft, "SQL Server 2012 Glossary", 2012)

"Data that is the result of applying a process to combine data elements collectively or in summary form. The SQL SELECT List does this very easily and offers quite a bit of dynamic control." (Michael M David & Lee Fesperman, "Advanced SQL Dynamic Data Modeling and Hierarchical Processing", 2013)

[aggregate operation:] "An operation on a data structure as a whole, as opposed to an operation on an individual component of the data structure" (Nell Dale & John Lewis, "Computer Science Illuminated, 6th Ed.", 2015)

[aggregated data] "Refers to data that has been scrubbed of any personally or entity identifiable information and then generally combined with similar information from other parties." (James R Kalyvas & Michael R Overly, "Big Data: A Businessand Legal Guide", 2015)

"Structured data that results from applying a process to more detailed data - data that is summarized or averaged." (Ciara Heavin & Daniel J Power, "Decision Support, Analytics, and Business Intelligence" 3rd Ed., 2017)

[data aggregate] "A collection of two or more data items that are treated as a unit." (IEEE 610.5-1990)

🛢DBMS: SQL Injection (Definitions)

"SQL injection is a technique that exploits security vulnerabilities in the application layer and middle tier, allowing users to execute arbitrary SQL statements on a server." (Michael Coles, "Pro T-SQL 2008 Programmer's Guide", 2008)

"A security vulnerability that occurs in the persistence/database layer of a Web application. This vulnerability is derived from the incorrect escaping of variables embedded in SQL statements. It is in fact an instance of a more general class of vulnerabilities based on poor input validation and bad design that can occur whenever one programming or scripting language is embedded inside another." (Mark S Merkow & Lakshmikanth Raghavan, "Secure and Resilient Software Development", 2010)

"A form of Web hacking whereby SQL statements are specified in a Web form to expose data to the attacker." (Craig S Mullins, "Database Administration", 2012)

"SQL injection is a technique that exploits security vulnerabilities in the application layer and middle tier, allowing users to execute arbitrary SQL statements on a server." (Jay Natarajan et al, "Pro T-SQL 2012 Programmer's Guide 3rd Ed", 2012)

"The process of manipulating a web application to run SQL commands sent by an attacker." (Mark Rhodes-Ousley, "Information Security: The Complete Reference, Second Edition, 2nd Ed.", 2013)

"A technique that exploits security vulnerabilities in the application layer and middle tier, allowing users to execute arbitrary SQL statements on a server." (Miguel Cebollero et al, "Pro T-SQL Programmer’s Guide 4th Ed", 2015)

🛢DBMS: Hash Table (Definitions)

"A data structure used internally by Perl for implementing associative arrays (hashes) efficiently. See also bucket." (Jon Orwant et al, "Programming Perl" 4th Ed., 2012)

[hash cluster:] "A type of table cluster that is similar to an indexed cluster, except the index key is replaced with a hash function. No separate cluster index exists. In a hash cluster, the data is the index." (Oracle, "Database SQL Tuning Guide Glossary", 2013)

"An in-memory data structure that associates join keys with rows in a hash join. For example, in a join of the employees and departments tables, the join key might be the department ID. A hash function uses the join key to generate a hash value. This hash value is an index in an array, which is the hash table." (Oracle, "Database SQL Tuning Guide Glossary", 2013)

"The data structure used to store elements using hashing" (Nell Dale et al, "Object-Oriented Data Structures Using Java" 4th Ed., 2016)

"An object that is like a dictionary or an associative array. A hash table stores and retrieves elements using key values called hashcodes. See also hashcode." (Daniel Leuck et al, "Learning Java" 5th Ed., 2020)

[sorted hash cluster:] "A hash cluster that stores the rows corresponding to each value of the hash function in such a way that the database can efficiently return them in sorted order. The database performs the optimized sort internally." (Oracle, "Oracle Database Concepts")

"An in-memory data structure that associates join keys with rows in a hash join. For example, in a join of the employees and departments tables, the join key might be the department ID. A hash function uses the join key to generate a hash value. This hash value is an index in an array, which is the hash table." (Oracle, "Oracle Database Concepts")

"A two-dimensional table of items in which a hash function is applied to the key of each item to determine its hash value. The hash value identifies each item's primary position in the table, and if this position is already occupied, the item is inserted either in an overflow table or in another available position in the table." (IEEE 610.5-1990)

🛢DBMS: Hash Index (Definitions)

"A hashing algorithm is used to organize an index into a sequence, where each indexed value is retrievable based on the result of the hash key value. Hash indexes are efficient with integer values, but are usually subject to overflow as a result of changes." (Gavin Powell, "Beginning Database Design", 2006)

"An index based on an ordered list of hash values." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management" 9th Ed., 2011)

"An index based on an ordered list of hash values." (Carlos Coronel & Steven Morris, "Database Systems: Design, Implementation, & Management" 11th Ed., 2014)

 "A type of index intended for queries that use equality operators, rather than range operators such as greater-than or BETWEEN. It is available for MEMORY tables. Although hash indexes are the default for MEMORY tables for historic reasons, that storage engine also supports B-tree indexes, which are often a better choice for general-purpose queries. MySQL includes a variant of this index type, the adaptive hash index, that is constructed automatically for InnoDB tables if needed based on runtime conditions." (MySQL, "MySQL 8.0 Reference Manual Glossary")

[adaptive hash index:] "An optimization for InnoDB tables that can speed up lookups using - and IN operators, by constructing a hash index in memory. MySQL monitors index searches for InnoDB tables, and if queries could benefit from a hash index, it builds one automatically for index pages that are frequently accessed." (MySQL, "MySQL 8.0 Reference Manual Glossary")

"Hash indexes are file structures that can be used either to resolve queries by accessing the index instead of its underlying base table or to enhance access performance when they do not cover a query by providing a secondary access path to requested base table rows. They can either substitute for or point to base table rows." (Teradata)

🛢DBMS: Query Plan [QP] (Definitions)

"The ordered set of steps required to carry out a query, complete with the access methods chosen for each table." (Karen Paulsell et al, "Sybase SQL Server: Performance and Tuning Guide", 1996)

"A portion of a DBMS that determines the most efficient sequence of relational algebra operations to use to satisfy a query." (Jan L Harrington, "Relational Database Design and Implementation" 3rd Ed., 2009)

"The plan produced by an optimizer for processing a query." (S. Sumathi & S. Esakkirajan, "Fundamentals of Relational Database Management Systems", 2007)

"A query plan is a sequence of logical and physical operators and data flows that the SQL query optimizer returns for use by the query processor to retrieve or modify data." (Michael Coles, "Pro T-SQL 2008 Programmer's Guide", 2008)

"Once the query optimizer determines the best way to execute a query, it creates a query plan. This identifies all the elements of the query, including what indexes are used, what types of joins are employed, and more." (Darril Gibson, "MCITP SQL Server 2005 Database Developer All-in-One Exam Guide", 2008)

"A sequence of logical and physical operators and data flows that the SQL query optimizer returns for use by the query processor to retrieve or modify data." (Miguel Cebollero et al, "Pro T-SQL Programmer’s Guide" 4th Ed., 2015)

[adaptive query plan:] "An execution plan that changes after optimization because run-time conditions indicate that optimizer estimates are inaccurate. An adaptive query plan has different built-in plan options. During the first execution, before a specific subplan becomes active, the optimizer makes a final decision about which option to use. The optimizer bases its choice on observations made during the execution up to this point. Thus, an adaptive query plan enables the final plan for a statement to differ from the default plan." (Oracle)

[default plan:] "For an adaptive plan, the execution plan initially chosen by the optimizer using the statistics from the data dictionary. The default plan can differ from the final plan." (Oracle)

[execution plan:] "The combination of steps used by the database to execute a SQL statement. Each step either retrieves rows of data physically from the database or prepares them for the session issuing the statement." (Oracle)

[query execution plan:] "The set of decisions made by the optimizer about how to perform a query most efficiently, including which index or indexes to use, and the order in which to join tables." (MySQL)