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TomP2P: Features, Overview and key concept & Overview

TomP2P is a distributed hash table which provides a decentralized key-value infrastructure for distributed applications. Each peer has a table that can be configured either to be disk-based or memory-based to store its values.

Language: English [EN]
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TomP2P topic overview

The analysis highlights Features, Overview and key concept and Overview as prominent areas in the source structure around TomP2P.

Related topics
8
Source areas
3
Connected nodes
11
Extracted relationships
12
Related term clusters
9
Bridge connections
11

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.

Features · 4 topics
Overview and key concept · 3 topics
Overview · 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
Thomas Bocek
License
Apache License 2
Repository
github.com/tomp2p/TomP2P
Stable release
4.4
Type
peer-to-peer, key-value store
Written in
Java

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TomP2P

Explore all related topics Closing gaps

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.

Overview

Overview and key concept

Features

For the semantics nerds

You can skip this section if you’re here for content ideas and keyword inspiration.

Advanced semantic analysis

How TomP2P connects Entity context

The extracted context around TomP2P shows recurring relationship patterns in the source. For example, TomP2P → API, DHT, Since TomP2P, Thus Another extracted example is TomP2P → Thomas Bocek. Use these groups to spot repeated connection types before inspecting the individual relationships.

TomP2P

Top relations

related to overview · 4
TomP2P → API, DHT, Since TomP2P, Thus
Developer · 1
TomP2P → Thomas Bocek
License · 1
TomP2P → Apache License 2
Repository · 1
TomP2P → github.com/tomp2p/TomP2P
Stable release · 1
TomP2P → 4.4
Type · 1
TomP2P → peer-to-peer, key-value store
Website · 1
TomP2P → tomp2p.net
Written in · 1
TomP2P → Java
is a · 1
TomP2P → distributed hash table which provides a decentralized key-value infrastructure for distributed applications

Important terminology

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

table distributed key-value store hash java peers uses iterative routing communication either key concept also non-blocking api website data protocol

TomP2P relationships Subject–Predicate–Object triples

TTTA extracted 12 structured relationships around TomP2P. Examples in this analysis include TomP2P → Developer → Thomas Bocek and TomP2P → License → Apache License 2. The table shows each extracted connection, where it came from and its confidence.

SubjectPredicateObjectConfidenceSrc
TomP2PDeveloperThomas Bocek1.00infobox
TomP2PLicenseApache License 21.00infobox
TomP2PRepositorygithub.com/tomp2p/TomP2P1.00infobox
TomP2PStable release4.41.00infobox
TomP2PTypepeer-to-peer, key-value store1.00infobox
TomP2PWebsitetomp2p.net1.00infobox
TomP2PWritten inJava1.00infobox
TomP2Pis adistributed hash table which provides a decentralized key-value infrastructure for distributed applications0.90text
TomP2Prelated to overviewSince TomP2P0.60section
TomP2Prelated to overviewDHT0.60section
TomP2Prelated to overviewAPI0.60section
TomP2Prelated to overviewThus0.60section

Related concept clusters Related term clusters

The concept neighborhoods around TomP2P bring nearby vocabulary together. In this analysis, examples include Communication, Iterative and Peers. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

  • distributed hash table
    • Hash
    • Store
    • Table
    • Key-value
    • Tomp2p
    • Data
    • Java
    • Website
    • Iterative
    • Routing
    • Applications
    • Decentralized
  • overview and key concept
    • Also
    • Concept
    • External
    • Key
    • Links
    • References
    • See
    • Features
    • Java
    • Overview
    • Website
    • Tomp2p
  • java
    • Website
    • Links
    • Overview
    • References
    • See
    • Data
    • Dht
    • Key
    • Key-value
    • Non-blocking
    • Protocol
    • Iterative
  • features
    • External
    • Links
    • Overview
    • References
    • See
    • Also
    • Java
    • Key
    • Key-value
    • Website
    • Hash
    • Store
  • TomP2P
    • Communication
    • Iterative
    • Peers
    • Routing
    • Uses
    • Api
    • Data
    • Dht
    • Non-blocking
    • Website
  • tomp2p
    • Communication
    • Iterative
    • Peers
    • Routing
    • Uses
    • Api
    • Data
    • Dht
    • Non-blocking
    • Website
  • overview
    • External
    • Links
    • References
    • See
    • Also
    • Java
    • Website
    • Store
    • Table
    • Tomp2p
  • api
    • Concept
    • Dht
    • Either
    • Key
    • Communication
    • Iterative
    • Peers
    • Routing
    • Tomp2p

Connections between topic areas Semantic bridges

For TomP2P, one of the stronger structural bridges in this analysis connects TomP2P with Features. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.

Min side: 3
TomP2P — Features · splits 7 ⟂ 5
TomP2P — Overview and key concept · splits 8 ⟂ 4

Map overview Semantic statistics

TomP2P

Nodes12
Edges11
Triples12
Avg. degree1.83
Density0.166667
Components1

Source & methodology

TTTA analyzes the structure around TomP2P to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Features, Overview and key concept & Overview, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.

Source: Wikipedia — TomP2P · EN edition · Analysis: TopicsToTalkAbout

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