GraphX for Graph-base Query
GraphX is designed to build a real-time and flexible Web3 relationship graph network for you, which can be used for social relationship recommendation and content recommendation applications.
A knowledge Graph is essentially a structured semantic knowledge base, which is used to describe the concepts in the physical world and their relationships in the form of symbols. Its basic unit is the "entity - relationship - entity" triplet, and entities and their related attribute value pairs. Entities are connected through relationships to form a network of knowledge structures. Generally speaking, Knowledge Graph is the most effective expression of relationships.
Real-time & Flexible
The knowledge graph is able to index-free adjacency, each node maintains node relationships with its neighbors, and the query time is independent of the size of the graph and related to the number of neighbors of each node, maintaining good performance even when dealing with a large number of complex relationships.
Relationship creates meaning
KNN3 believes that "relationship creates meaning", and uses the Knowledge Graph to more accurately present the relationship between users and some of the users' behaviors on the chain. As a composable relational data service, KNN3 Network can be applied to huge Web3 native scenarios.
For users of GraphX, you can use GraphX:
- Query the address and its basic data (ENS) and related web2/Web3 data (POAPs, Follows, Snapshot, Twitter, etc.).
- Query the POAPs (Name or EventId) and the address of the activity.
- Query NFTs (metaData: symbol, name, image URL...) and holders.
- Query the ERC-20 token and its holders.
- Query the address of the bound Twitter.
- Query the resolution address of ENS.
- Query the voting address given by the Snapshot to each campaign owner(SpaceID).
- Query DIDs data (Avatar/ .bit).
KNN3 aggregates Web3/web2 data collection into a centralized database through an efficient real-time collection and analysis engine, and provides data through Graphql. Users can freely combine data and present it in various dapps. The MashMesh, which integrates all kinds of user data and presents them in a graphical human-readable way, powered by KNN3 GraphX, so that users can clearly see all kinds of address behaviors, analyze the relationship between addresses, etc.