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OvenMediaEngine: History, Usage & Awards
OvenMediaEngine (OME) is a low-latency streaming server with large-scale and high-definition that OvenMedia Labs Inc (formerly AirenSoft Co., Ltd.) released as open-source software via GitHub in December 2018. The main programming language used was C++, and the first update was on May 23, 2019.
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OvenMediaEngine topic overview
The analysis highlights History, Usage and Awards as prominent areas in the source structure around OvenMediaEngine.
Related topics
25
Source areas
4
Connected nodes
29
Extracted relationships
115
Concept neighborhoods
13
Bridge connections
29
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.
Usage · 11 topics
History · 9 topics
Overview · 4 topics
Awards · 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.
Developer
OvenMedia Labs
License
AGPL v3.0
Operating system
Ubuntu 18+, Rocky Linux 9+, AlmaLinux 9+, Fedora 28+
Other names
OME
Platform
Docker
Release
v0.9.0 / 23 May 2019; 7 years ago (2019-05-23)
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 OvenMediaEngine 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 OvenMediaEngine shows recurring relationship patterns in the source. For example, OvenMediaEngine → ABR, AccessControl, Adaptive Bitrate Streaming, AGPLv3, Conditional Encoding, Digital, Digital Video Recorder, Docker, DRM, DVR, E-RTMP, Egress, Enhanced RTMP, GPLv3, HEVC, High-Efficiency Video Coding, HLS, In April, In December, In February Another extracted example is OvenMediaEngine → ABR, Adaptive Bitrate Streaming, HLS, HTTP Live Streaming, If, It, LL-HLS, Low Latency HLS, Low-Latency HLS, MP4, MPEG2-TS, OBS, Open Broadcaster Software, RTMP, RTSP, SRT, Video, Web, Webcam, WebRTC. Use these groups to spot repeated connection types before inspecting the individual relationships.
OvenMediaEngine
Top relations
related to history· 60
OvenMediaEngine → ABR, AccessControl, Adaptive Bitrate Streaming, AGPLv3, Conditional Encoding, Digital, Digital Video Recorder, Docker, DRM, DVR, E-RTMP, Egress, Enhanced RTMP, GPLv3, HEVC, High-Efficiency Video Coding, HLS, In April, In December, In February
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 115 structured relationships around OvenMediaEngine. Examples in this analysis include OvenMediaEngine → Developer → OvenMedia Labs and OvenMediaEngine → License → AGPL v3.0. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
OvenMediaEngine
Developer
OvenMedia Labs
1.00
infobox
OvenMediaEngine
License
AGPL v3.0
1.00
infobox
OvenMediaEngine
Operating system
Ubuntu 18+, Rocky Linux 9+, AlmaLinux 9+, Fedora 28+
1.00
infobox
OvenMediaEngine
Other names
OME
1.00
infobox
OvenMediaEngine
Platform
Docker
1.00
infobox
OvenMediaEngine
Release
v0.9.0 / 23 May 2019; 7 years ago (2019-05-23)
1.00
infobox
OvenMediaEngine
Repository
https://github.com/OvenMediaLabs/OvenMediaEngine
1.00
infobox
OvenMediaEngine
Stable release
v0.20.5 / 26 March 2026; 4 months ago (2026-03-26)
and MPEG2-TS protocols through commonly used stream tools
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 OvenMediaEngine bring nearby vocabulary together. In this analysis, examples include License, Software and General. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
OvenMediaEngine
License
Software
General
Licensed
South
Version
Streaming
Agplv3
Award
Awards
Good
Level
ovenmediaengine
License
Software
General
Licensed
South
Version
Streaming
Agplv3
Award
Awards
Good
Level
open-source software
Ovenmedia
Server
Github
Good
Level
Streaming
Docker
Software
Also
Awards
South
Srt
webrtc
January
Streaming
Low-latency
Support
Hls
Software
Announced
Docker
Labs
Open-source
Ovenmedia
Also
awards
Minister
Received
South
Docker
Labs
Open-source
Ovenmedia
Ovenmediaengine
Also
Good
Level
Ome
legacy hls
Low-latency
Streaming
Using
Live
Version
Software
Webrtc
Ovenmediaengine
Ll-hls
Labs
Open-source
Ovenmedia
streaming server
Software
Streaming
Live
Webrtc
Docker
Also
Awards
Good
Level
January
Srt
License
docker
Ome
Labs
Open-source
Ovenmedia
Ll-hls
Good
Level
Server
Using
License
Low-latency
Version
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 OvenMediaEngine, one of the stronger structural bridges in this analysis connects OvenMediaEngine with Usage. 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.
OvenMediaEngine
Nodes30
Edges29
Triples115
Avg. degree1.93
Density0.066667
Components1
Source & methodology
TTTA analyzes the structure around OvenMediaEngine to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Usage & Awards, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
