Find related topics. | Discover entities. | See connections. | Build a topical map.
Simba Technologies: History, Standards, Art & Companies
Simba (formerly Simba Technologies Inc.) is a software company specializing in solutions for ODBC and JDBC data drivers. Originally founded in 1991 as PageAhead Software in Vancouver, British Columbia, Simba co-developed the first standards-based ODBC driver with Microsoft. The company was acquired by Magnitude Software in 2016, and became part of…
Use the mouse wheel or two fingers (on touchscreens) to zoom in and out of the map.
More settings
Simba Technologies topic overview
The analysis highlights History, Standards, Art and Companies as prominent areas in the source structure around Simba Technologies.
Related topics
27
Source areas
4
Connected nodes
31
Extracted relationships
51
Related term clusters
15
Bridge connections
31
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 · 10 topics
Overview · 8 topics
Products · 8 topics
Services · 1 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.
Founded
1991; 35 years ago (1991)
Headquarters
Raleigh, North Carolina, United States
Key people
Michael Sullivan (CEO), Jay Allardyce (GM), Sami Akbay (VP Product)
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.
You can skip this section if you’re here for content ideas and keyword inspiration.
Advanced semantic analysis
How Simba Technologies 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 Simba Technologies shows recurring relationship patterns in the source. For example, Simba Technologies → Apache Hive, British Columbia, ERP, Google BigQuery, Magnitude Software, Magnitude’s, Microsoft, ODBC, PageAhead, PageAhead Software, SDK, Seattle, Simba, Simba ODBC, Simba Workday Drivers, SimbaEngine, Snowflake, Vancouver, Washington, Windows Another extracted example is Simba Technologies → Attachmate, British Columbia, DLL, JDBC, Microsoft, Microsoft Windows, ODBC, OLE DB, Oracle, PageAhead Software, SAP, Seattle, Simba, Throughout, Vancouver, Washington, XMLA. Use these groups to spot repeated connection types before inspecting the individual relationships.
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 51 structured relationships around Simba Technologies. Examples in this analysis include Simba Technologies → Founded → 1991; 35 years ago (1991) and Simba Technologies → Headquarters → Raleigh, North Carolina, United States. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
Simba Technologies
Founded
1991; 35 years ago (1991)
1.00
infobox
Simba Technologies
Headquarters
Raleigh, North Carolina, United States
1.00
infobox
Simba Technologies
Key people
Michael Sullivan (CEO), Jay Allardyce (GM), Sami Akbay (VP Product)
and Attachmate on data access technologies.In 2012
instance of
and collaborated with companies
0.80
text
Simba developed one of the first ODBC drivers for Apache Hive
instance of
and collaborated with companies
0.80
text
enabling SQL-based access to Hadoop data sources.Simba was acquired by Magnitude Software in 2016
instance of
and collaborated with companies
0.80
text
No triples extracted yet.
Related concept clusters Related term clusters
Related term clusters 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 Simba Technologies bring nearby vocabulary together. In this analysis, examples include Data, Odbc and Driver. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Simba Technologies
Data
Odbc
Driver
Software
Insightsoftware
Drivers
Simba
Technologies
Company
Connectivity
Access
Microsoft
big data
Sources
Drivers
Simba
Connectivity
Jdbc
Odbc
Access
Big
Data
Including
Technologies
Platforms
simba technologies
Data
Odbc
Driver
Software
Insightsoftware
Drivers
Simba
Technologies
Jdbc
Company
Connectivity
Access
odbc
Driver
Sources
Access
Drivers
Data
Simba
Big
Hive
Jdbc
Microsoft
Platforms
Custom
jdbc
Access
Drivers
Data
Solutions
Platforms
Big
Custom
Odbc
Sdk
Including
Sources
Technologies
insightsoftware
Magnitude
Connectivity
Simba
Software
Raleigh
Services
Enterprise
Analytics
Business
Platforms
Solutions
Custom
microsoft
Intelligence
Business
Odbc
Platforms
Pageahead
Simba
Software
Vancouver
Custom
Development
Sdk
Analytics
microsoft power bi
Intelligence
Business
Odbc
Platforms
Pageahead
Simba
Software
Vancouver
Custom
Development
Sdk
Analytics
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 Simba Technologies, one of the stronger structural bridges in this analysis connects Simba Technologies 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.
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
Simba Technologies
Nodes32
Edges31
Triples51
Avg. degree1.94
Density0.0625
Components1
Source & methodology
TTTA analyzes the structure around Simba Technologies to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Standards, Art & Companies, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
