The Decentralized Knowledge Graph & The Decentralized Knowledge P2P Network
Weaviate is a knowledge graph which meshes all your data and makes it available as one seamless source for contextualized research, reporting, and re-use. Our aim is to transform static (big-)data into a natural language queryable knowledge base which you can access directly or over a peer-to-peer network.
Weaviate comes with a variety of features and is based on specific design principles.
Key features of Weaviate include:
|Contextual||The Contextionary is a fast and powerful natural language processing tool which combines multiple uni-directional word embeddings, bi-directional word embeddings and other NLP tools to achieve production-ready machine comprehension tasks. You can read more about the Contextionary here and the roadmap for new features is located here.|
|Contextual ontologies||Weaviate's ontologies are completely contextual, meaning that you not only use words to describe what your data means but also the context in which your data appears.|
|Easy to use||We rely heavily on vanilla GraphQL and RESTful interfaces. We believe in a superior developer user experience and try to make it as easy as possible to use Weaviate|
|Decentralized knowledge graphs (P2P-network)||If desired, you can create a decentralized P2P-network of many Weaviates. This is especially handy when you want to share data or to make specific knowledge graph architectures.|
|Modular data storage||Because Weaviate can be used for many use cases where consistency, availability and partition tolerance play different roles, we want to make it as easy as possible to use multiple databases to store your data.|
Note: Weaviate is currently only available as an unstable release. We hope to release a first stable version in the coming months.
Weaviate's documentation is available in the
./docs folder on Github and divided into two sections: