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dBase (also stylized dBASE) was one of the first database management systems for microcomputers and the most successful in its day. The dBase system included the core database engine, a query system, a forms engine, and a programming language that tied all of these components together.
The analysis highlights History, Products and Companies as prominent areas in the source structure around DBase.
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 DBase shows recurring relationship patterns in the source. For example, DBase → Ashton, Ashton-Tate, BASE, CP/M, Discount Software, George Tate, Hal Lashlee, Hal Pawluk, IBM, IBM PC, II, II RunTime, In, Pawluk, PC, PTDOS, Ratliff, RunTime, Software Distributors, SuperCalc Another extracted example is DBase → Along, Ashton-Tate, Borland, By, Example, Fox Software, FoxPro, FoxView, III, Introduced, IV, IV's, Luis Castro's ViewGen, Query, SQL. 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.
xbase products ashton-tate language needed citation software database one programming file clipper product data foxpro microsoft ii use could iv
TTTA extracted 118 structured relationships around DBase. Examples in this analysis include DBase → Developer → Cecil Wayne Ratliff and DBase → Final release → dBASE 2019 / 2019; 7 years ago (2019). The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| DBase | Developer | Cecil Wayne Ratliff | 1.00 | infobox |
| DBase | Final release | dBASE 2019 / 2019; 7 years ago (2019) | 1.00 | infobox |
| DBase | First appeared | 1979; 47 years ago (1979) | 1.00 | infobox |
| DBase | Implementation language | C | 1.00 | infobox |
| DBase | License | Proprietary | 1.00 | infobox |
| DBase | OS | Microsoft DOS Microsoft Windows | 1.00 | infobox |
| DBase | Paradigm | Imperative, declarative | 1.00 | infobox |
| DBase | Website | www.dbase.com | 1.00 | infobox |
| DBase | is a | application development language and integrated navigational database management system | 0.90 | text |
| user-defined functions | instance of | Ashton-Tate's competitors introduced so-called clone products and compilers that had more robust programming features | 0.80 | text |
| the state of memory variables or tables being manipulated in other program modules | instance of | A tenet of modular programming is that the correct execution of a program module must not be affected by external factors | 0.80 | text |
| LIST | instance of | Different commands | 0.80 | text |
The concept neighborhoods around DBase bring nearby vocabulary together. In this analysis, examples include Needed, Citation and Language. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For DBase, one of the stronger structural bridges in this analysis connects DBase with Overview. 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 DBase to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Products & Companies, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — DBase · EN edition · Analysis: TopicsToTalkAbout