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In computing, a database is an organized collection of data or a type of data store based on the use of a database management system (DBMS), the software that interacts with end users, applications, and the database itself to capture and analyze the data. The DBMS additionally encompasses the core facilities provided to administer the database. The sum…
The analysis highlights History, Applications, Research and Products as prominent areas in the source structure around Database.
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
The extracted context around Database shows recurring relationship patterns in the source. For example, Database → Abraham Silberschatz, Auer, CMU Database, Concepts, Database Concepts, Database Management Systems, Database Modeling, Database System Concepts, Database Systems, Database SystemsBerkeley CS W186, David, Design, Eds, Encyclopedia, Fall, Gray, Henry, ISBN, Johannes Gehrke, Korth Another extracted example is Database → ACNielsen, ACP, Also, An, Another, Both, Data, DBMS, DBMSs, Document-oriented, End-user, Examples, FDBMS, For, General, Hypertext, In, It, KB, Main. Use these groups to spot repeated connection types before inspecting the individual relationships.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
data dbms databases model relational system storage used use sql one information access systems application management applications users query may
TTTA extracted 376 structured relationships around Database. Examples in this analysis include Database → is a → organized collection of data or a type of data store based on the use of a database management system and Database → is a → database that primarily resides in main memory. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Database | is a | organized collection of data or a type of data store based on the use of a database management system | 0.90 | text |
| Database | is a | database that primarily resides in main memory | 0.90 | text |
| Database | is a | kind of NoSQL database that uses graph structures with nodes | 0.90 | text |
| magnetic disks | instance of | The concept of a database was made possible by the emergence of direct access storage media | 0.80 | text |
| which became widely available in the mid-1960s | instance of | The concept of a database was made possible by the emergence of direct access storage media | 0.80 | text |
| Sybase | instance of | on the desktopBesides IBM and various software companies | 0.80 | text |
| Informix Corporation | instance of | on the desktopBesides IBM and various software companies | 0.80 | text |
| most large computer hardware vendors by the 1980s had their own database systems such as DEC's VAX Rdb/VMS | instance of | on the desktopBesides IBM and various software companies | 0.80 | text |
| MySQL has grown since 2000 | instance of | The popularity of open source databases | 0.80 | text |
| to the extent that Ken Jacobs of Oracle said in 2005 that perhaps | instance of | The popularity of open source databases | 0.80 | text |
| Neo4j | instance of | including graph databases | 0.80 | text |
| represent data as nodes | instance of | including graph databases | 0.80 | text |
The concept neighborhoods around Database bring nearby vocabulary together. In this analysis, examples include Dbms, Model and System. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Database, one of the stronger structural bridges in this analysis connects Database with History. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
TTTA analyzes the structure around Database to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Applications, Research & Products, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Database · EN edition · Analysis: TopicsToTalkAbout