The Dataphor glossary provides definitions for potentially unfamiliar terms the user may come across in using Dataphor and reading its documentation.
Automated Application Development. The name given to the paradigm of development enabled by the Dataphor Platform. AAD focuses on describing "what" an application needs to do, rather than "how" it does it.
The name given to the category of components that are used to execute various commands within definition of forms within the Frontend.
6. Aggregate Operator
An operator with a specialized calling convention that allows aggregate operations to be computed efficiently.
7. Application Schema
8. Application Transaction
The idea that a transaction must behave as a single unit of work. It must either all be applied, or all be rolled back.
10. Base Table Variable
Basic Object Persistence. A serialization mechanism used internally by the Dataphor toolset to persist object state.
12. Business Rules
A general term describing the requirements of a particular business. In other words, the constraints which must be enforced on the database.
The name given to all components and controls used in the definition of forms in the Frontend.
The name given to all visual components used in the definition of forms in the Frontend. All controls are components, but not all components are controls.
23. Cursor Capabilities
24. Cursor Isolation Level
The isolation level associated with a given cursor. In conjunction with the isolation level for the transaction in which the cursor is participating, determines how the cursor should interact with other cursors and transactions running on the system. For a complete list of available cursor isolation levels, see the D4 Language Guide.
See Isolation Level.
25. Cursor Type
A description of the characteristics of a cursor with respect to changes made to the database since the cursor was opened. A static cursor is immune to changes in the database, while a dynamic cursor can see updates made to the database, so long as the cursor and transaction isolation levels allow it.
D4 is the database access language used to communicate with the Dataphor Server. D4 provides a complete relational algebra for manipulating data, as well as a rich type system for describing even the most complex data. D4 is also computationally complete, and supports a full complement of flow control constructs, including exception handling, to provide a complete development language with data manipulation capabilities.
28. Data Definition Language (DDL)
A category of statements in a database language which allow data structures to be defined and manipulated.
29. Data Integrity
30. Data Manipulation Language (DML)
A category of statements in a database language which allow data to be retrieved and manipulated.
31. Data Mining
The act of probing a database searching for information which may be manifested as trends in the data.
32. Data Model
A logical abstraction of data which allows the modeling of general characteristics of all data.
The logical abstraction of all the data of interest to a particular enterprise or entity. Also called a business model when used in this sense.
33. Data Warehousing
The act of gathering data from distributed locations in a single store, usually in some aggregated form for further analysis.
An organized collection of facts.
35. Database Management System (DBMS)
A computer system specifically designed to store and maintain data.
The Integrated Development Environment (IDE) for the Dataphor platform. Dataphoria is used to develop, maintain, and administer Dataphor applications.
37. Dataphor Server
The DBMS portion of the Dataphor toolset. An instance of a Dataphor Server can be hosted within a running Dataphoria, or as a service.
39. Derived Table Variable
Dataphor Interface Language. An XML format for describing user interfaces independent of the platform on which they will be realized.
System or user event that fires in response to some occurrence such as a data modification or proposable call.
48. Expression Plan
50. Frontend Server
51. Host-Implemented Operator
52. Impedance Mismatch
A term typically used to describe the disparity arising between the language used to query the database, (normally SQL) and the language used to code the business processes in the layers above the database, such as C, C++, Pascal, etc. Dataphor applications do not suffer from this type of impedance mismatch because the language used to query the data is also used to code the business processes.
The correctness, or accuracy, of the data in the database. The tables in a relational database can be viewed as having a predicate where each column is a placeholder. This predicate represents the meaning of the data in the table. Each row in the table can then be viewed as a proposition by substituting each placeholder with the value for the corresponding column in that row. The resulting proposition is considered true. Therefore, a relational database is quite literally a collection of true propositions, or facts. Integrity refers to this concept of truth in the database.
54. Integrity Constraint
The idea that a given process runs as though it is the only one in a given system, even though there may be multiple processes actually running. Isolation is typically enforced by locking.
56. Isolation Level
The degree of isolation associated with a particular transaction. The degree of isolation is inversely proportional to the degree of concurrency. In other words, the higher the isolation level, the lower the concurrency, and vice versa. An important result of isolation theory states that if all transactions run at least Degree 1 isolation (also called browse, or read uncommitted) then no transaction running at a lower isolation level will interfere with transactions running at higher isolation levels.
A set of columns in a table variable which constitute a unique identifier for every row in the table. Note that a key may contain no columns, as well as multiple columns. In effect, a key states that no two rows in the table variable for which it is defined are allowed to have the same values for all the columns of the key. Note also that keys are inferred for derived table variables.
58. Key Inference
The process by which the compiler determines the set of keys that hold within the result of a given table-valued expression. This information is used by the compiler and distributed query processor to perform semantic optimization, as well as by the Frontend to perform query elaboration and user interface derivation.
60. Logical Data Independence
61. Logical Model
An abstract construction used to describe the characteristics and behavior of some system.
Data or information about the data contained in a database.
63. Metadata Inference
64. Native Accessor
A host-implementation mechanism used to retrieve and specify values in the host-implementation language.
65. Native Representation
66. Navigational Access
Normalization refers to the process of decomposing a set of relations using projection to eliminate potential redundancy.
72. Physical Data Independence
The idea that the logical data model can remain unaffected by changes at the physical level.
74. Predicate Logic
A system of logic in which a proposition is allowed to contain placeholders. These parameterized propositions are called predicates. Each place holder is allowed to range over a domain (or type) of values. Substituting values for these domains in each placeholder results in a truth-valued proposition.
76. Proposable Interface
The Proposable interface allows the application to perform intermediate processing while data entry is occurring, where rows are built a column at a time as the user enters data.
77. Query Processor
That portion of a Database Management System which is responsible for producing the results of a given query.
80. Reference Inference
81. Referential Integrity
A special type of integrity referring to the relationships between tables. Specifically, a referential integrity constraint says that if a given row is in some table, it must have a corresponding row in some table (not necessarily a different table). A reference (also called a foreign key) is used to enforce referential integrity.
82. Relation Type
A relation (value) consists of a heading: a set of attributes of the form
84. Relation Variable
85. Relational Algebra
A set of manipulative operators used to derive new relations from existing ones. The five primitive operators of the relational algebra are restriction, projection, union, difference, and either intersection or join. Each of these operators is closed over relations, meaning that the result of each operator is a relation, and can therefore be used as the argument to the next operator.
86. Relational Calculus
87. Relational Model
A formal theory of data consisting of three major components: (a) A structural aspect, meaning that data in the database is perceived as tables, and only tables, (b) An integrity aspect, meaning that those tables satisfy certain integrity constraints, and (c) A manipulative aspect, meaning that the tables can be operated upon by means of operators which derive tables from tables.
A general term used to describe the representation of values of types. There are several categories of representations within the Dataphor Platform:
- Physical Representation
- Device Representation
The device representation of a value is the value as it appears at the connectivity implementation boundary. This is the way a value appears as it is first presented to the DAE from a device. This is also the representation as it appears when it is handed back to the device through the connectivity implementation.
- Native Representation
The native representation of a value in the host implementation language of the Dataphor Server, namely a .NET representation of the value. For example, the native representation of values of type
System.Integeris as a value of type
Int32in the .NET Framework.
- Logical Representation
- Presentation Representation
The representation of a value of some type in a user interface (also called the Frontend representation). A given type may also have multiple presentation representations such as a display representation, and an edit representation. Note that any given presentation representation is always a logical representation, but not every logical representation is available as a presentation representation.
90. Row (Value)
91. Scalar Type
92. Scalar (Value)
A value with no user-visible components.
The system definition of the structure of the objects contained within the database, including types, operators, constraints, tables, views, devices, etc.,.
Storage Integration Architecture. The name given to the technology which provides the storage abstraction layer in the Dataphor Server.
97. Sparse Key
98. Special Value
100. Statement Plan
101. Storage Device
102. Storage Integration Architecture (SIA)
103. System-Provided Operator
An operator whose definition is provided by the system. This term is used to refer both to operators that are built-in as part of the system libraries, and to operators whose definition is provided as part of the compilation process, such as selectors and accessors for system-provided representations.
104. System-Provided Representation
106. Table (Value)
107. Table Variable
110. Transaction Management
The process by which transactions from multiple users are coordinated within a single system. Transaction management involves scheduling access to shared resources to ensure that all actions taken against the system have consistent effects.
111. Tuple (Value)
A tuple consists of a heading: a set of attributes of the form
113. Type Inference
114. User Interface Derivation
A value is a constant with no location in space or time. Values, by definition, are immutable.