Topic orientation
Erwin Data Modeler at a glance
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Explore the main themes, entities and connections around Erwin Data Modeler. Start with the topic map, then use the sections below for research and deeper semantic analysis.
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Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.
History
Overview
Notable users
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
- As of
- January 2026
- Developers
- Logic Works (Through 1998) · Platinum Technology (1998–1999) · CA Technologies (1999–2016) · erwin, Inc. (2016 to 2021) · Quest Software (2021 to present)
- License
- Proprietary, Trialware, EULA
- Operating system
- Microsoft Windows and iOS
- Stable release
- 15.2 version / January 6, 2026; 7 months ago (2026-01-06)
- Type
- CASE tool
Topics to explore
A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.Browse the full topic structure. Each item opens a new analysis centered on that subject.
Overview
- Data modeling
- Logic Works
- IDEF1X
- Information technology engineering
- Computer-aided software engineering
- Conceptual data model Conceptual schema
- Logical data model Database design
- Physical data model
- Data definition language
- Database-management systems Database Management System
- Entity–relationships Entity–relationship model
- Database constraints Relational database
- Indexes Database index
- James Martin James Martin (author)
- Dimensional modeling
- PostgreSQL
History
- Princeton, New Jersey
- PowerBuilder
- Integrated development environment
- Gupta Technologies
- Visual Basic
- Client–server model
- Platinum Technology
- Computer Associates
- Embarcadero Technologies
- CA, Inc.
- Department of Justice United States Department of Justice
- Private equity firm
- Enterprise architecture
- Business process modeling
- NoSQL
- Quest Software
Notable users
Advanced semantic analysis
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
How this topic connects Entity context
Quick relationship hints grouped by predicate. Useful for spotting recurring semantic connections around the current entity.See the strongest relationship patterns around the current topic before diving into the raw triples.
Erwin Data Modeler
Top relations
Important terminology Word statistics
Frequent words and multi-word phrases across the lead, headings, infobox and body. Useful for terminology coverage.Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
Important terminology
erwin data software modeling acquired logic works technology modeler model also database ca inc quest used company technologies 2016 2018
Entity relationships Subject–Predicate–Object triples
Extracted RDF-like relationships with confidence and source. The table includes structured facts and lower-confidence contextual relations.| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Erwin Data Modeler | As of | January 2026 | 1.00 | infobox |
| Erwin Data Modeler | Developers | Logic Works (Through 1998) | 1.00 | infobox |
| Erwin Data Modeler | Developers | Platinum Technology (1998–1999) | 1.00 | infobox |
| Erwin Data Modeler | Developers | CA Technologies (1999–2016) | 1.00 | infobox |
| Erwin Data Modeler | Developers | erwin, Inc. (2016 to 2021) | 1.00 | infobox |
| Erwin Data Modeler | Developers | Quest Software (2021 to present) | 1.00 | infobox |
| Erwin Data Modeler | License | Proprietary, Trialware, EULA | 1.00 | infobox |
| Erwin Data Modeler | Operating system | Microsoft Windows and iOS | 1.00 | infobox |
| Erwin Data Modeler | Stable release | 15.2 version / January 6, 2026; 7 months ago (2026-01-06) | 1.00 | infobox |
| Erwin Data Modeler | Type | CASE tool | 1.00 | infobox |
| Erwin Data Modeler | Website | support.quest.com/erwin-data-modeler/15.2/download-new-releases/ | 1.00 | infobox |
| Erwin Data Modeler | related to history | ERwin | 0.60 | section |
Related concept clusters Concept neighborhoods
Clusters of nearby vocabulary surrounding the topic. Scan them for adjacent concepts and language you may have missed.These clusters group vocabulary that occurs around closely connected concepts in the source material.
Connections between topic areas Semantic bridges
Bridge nodes connect otherwise separate parts of the map. Expand a row to inspect the topic groups on each side.Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.