An object database or object-oriented database is a database management system in which information is represented in the form of objects as used in object-oriented programming. Object databases are different from relational databases which are table-oriented. A third type, object–relational databases, is a hybrid of both approaches. Object databases…
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Object database topic overview
The analysis highlights History, Standards, Companies and Products as prominent areas in the source structure around Object database.
Related topics
81
Source areas
7
Connected nodes
88
Extracted relationships
169
Concept neighborhoods
30
Bridge connections
88
What this topic covers Research coverage
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.
History · 20 topics
Overview · 20 topics
Timeline · 14 topics
Standards · 12 topics
Technical features · 8 topics
Adoption of object databases · 5 topics
Comparison with RDBMSs · 2 topics
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.
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Explore all related topics Closing gaps
A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.
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.
How Object database connects Entity context
Entity context groups extracted connections by relationship type. Counts show recurrence in the analyzed source; the examples are research signals, not claims about importance.
The extracted context around Object database shows recurring relationship patterns in the source. For example, Object database → Additional, Bell Labs, Brown University, Computer Associates, Computer Technology Corporation, Early, Encore-Ob/Server, EXODUS, FastObjects, Fujitsu, Gbase, Gemstone, GemStone Systems, GMD-IPSI, Graphael, Hewlett-Packard, IBM, Inc, Incorporated, Informix Another extracted example is Object database → Actian, An ODMG-Based Object-Oriented DBMS, Arvind Rajendran, CachéVersant Object DatabaseODABAZODBPoetJADEMatisseIllustra Informix2000slambda-DB, CAD/CAM1982Gemstone, Carl RosenbergerObjectDB2001 IBM, Chandrasekhar Srinivasan, Corporation, David Maierdb4o, Design, GBase, Gemstone, Gemstone Systems, Gemstone SystemsGemstone, GemStone2011, Inc, Incorporated, INFORMIX, Informix2003, Java. Use these groups to spot repeated connection types before inspecting the individual relationships.
Object database → As, By, Compliance, Group, In, It, Its, Java Community Process, Java Data Objects, Many, ODMG, ODMG Java Language Binding, SQL, The, The Object Data Management, The ODMG
Relationships are represented as Subject → Predicate → Object triples. Confidence describes extraction strength, not the real-world importance of a relationship; lower-confidence rows may be contextual rather than explicit.
TTTA extracted 169 structured relationships around Object database. Examples in this analysis include Delphi → instance of → Some object-oriented databases are designed to work well with object-oriented programming languages and InterSystems Caché.Object database management systems added the concept of persistence to object programming languages → instance of → Some of these products remain on the market and have been joined by new open source and commercial products. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
Delphi
instance of
Some object-oriented databases are designed to work well with object-oriented programming languages
0.80
text
Ruby
instance of
Some object-oriented databases are designed to work well with object-oriented programming languages
0.80
text
Python
instance of
Some object-oriented databases are designed to work well with object-oriented programming languages
0.80
text
JavaScript
instance of
Some object-oriented databases are designed to work well with object-oriented programming languages
0.80
text
Perl
instance of
Some object-oriented databases are designed to work well with object-oriented programming languages
0.80
text
Java
instance of
Some object-oriented databases are designed to work well with object-oriented programming languages
0.80
text
C
instance of
Some object-oriented databases are designed to work well with object-oriented programming languages
0.80
text
InterSystems Caché.Object database management systems added the concept of persistence to object programming languages
instance of
Some of these products remain on the market and have been joined by new open source and commercial products
0.80
text
engineering
instance of
2014 Realm2017 ObjectBox Adoption of object databasesObject databases based on persistent programming acquired a niche in application areas
0.80
text
spatial databases
instance of
2014 Realm2017 ObjectBox Adoption of object databasesObject databases based on persistent programming acquired a niche in application areas
0.80
text
telecommunications
instance of
2014 Realm2017 ObjectBox Adoption of object databasesObject databases based on persistent programming acquired a niche in application areas
0.80
text
and scientific areas such as high energy physics
instance of
2014 Realm2017 ObjectBox Adoption of object databasesObject databases based on persistent programming acquired a niche in application areas
0.80
text
No triples extracted yet.
Related concept clusters Concept neighborhoods
Concept neighborhoods group terms that sit near one another in the extracted graph. They are useful for discovering adjacent language and context, but proximity does not by itself imply a factual relationship.
The concept neighborhoods around Object database bring nearby vocabulary together. In this analysis, examples include Object, Databases and Management. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Object database
Object
Databases
Management
Systems
Relational
Data
Model
Also
Commercial
Objects
Programming
Dbms
object database
Management
Object
Databases
Systems
Relational
Data
Programming
Language
System
Model
Also
Commercial
database management system
Management
Object
Systems
Relational
System
Objects
Data
Programming
Language
New
Technology
Model
object-oriented programming
Language
Programming
Use
Languages
Oodbmss
Query
System
Java
Also
Databases
Xquery
Smalltalk
relational databases
Object
Programming
Xml
Systems
Also
Use
Xquery
Object-oriented
Relational
Smalltalk
Json
Data
object–relational databases
Databases
Object
Management
Systems
Relational
Data
Programming
Xml
Also
Commercial
Use
Xquery
database model
Management
Object
Systems
Relational
Started
Dbms
Servio
Data
Logic
Programming
Set
Language
object-oriented programming languages
Language
Smalltalk
Programming
Use
Languages
Oodbmss
Query
System
Java
Also
Databases
Xquery
Connections between topic areas Semantic bridges
Semantic bridges connect parts of the graph that would otherwise be more separate. A bridge is a structural signal in this analysis, not a claim that the two topic areas are equivalent.
For Object database, one of the stronger structural bridges in this analysis connects Object database 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.
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
Object database
Nodes89
Edges88
Triples169
Avg. degree1.98
Density0.022472
Components1
Source & methodology
TTTA analyzes the structure around Object database to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Standards, Companies & Products, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
