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A one-to-many relationship between records in patient and records in appointment because patients can have many appointments and each appointment involves only one patient. [1] A one-to-one relationship is mostly used to split a table in two in order to provide information concisely and make it more understandable. In the hospital example, such ...
One of the arguments against using an OODBMS is that it may not be able to execute ad-hoc, application-independent queries. [ citation needed ] For this reason, many programmers find themselves more at home with an object-SQL mapping system, even though most object-oriented databases are able to process SQL queries to a limited extent.
One scheme has one element that needs to be split up with different parts of it placed in multiple other elements in the second scheme ("one-to-many" mapping) One scheme allows an element to be repeated more than once while another only allows that element to appear once with multiple terms in it; Schemes have different data formats (e.g. John ...
The terms schema matching and mapping are often used interchangeably for a database process. For this article, we differentiate the two as follows: schema matching is the process of identifying that two objects are semantically related (scope of this article) while mapping refers to the transformations between the objects.
The states of a created conceptual schema are transformed into an explicit mapping, the database schema. This describes how real-world entities are modeled in the database. "A database schema specifies, based on the database administrator 's knowledge of possible applications, the facts that can enter the database, or those of interest to the ...
In computing and data management, data mapping is the process of creating data element mappings between two distinct data models. Data mapping is used as a first step for a wide variety of data integration tasks, including: [1] Data transformation or data mediation between a data source and a destination
Bitemporal modeling is a specific case of temporal database information modeling technique designed to handle historical data along two different timelines. [1] This makes it possible to rewind the information to "as it actually was" in combination with "as it was recorded" at some point in time.
Relational databases are very well suited to flat data layouts, where relationships between data are only one or two levels deep. For example, an accounting database might need to look up all the line items for all the invoices for a given customer, a three-join query. Graph databases are aimed at datasets that contain many more links.