* The mathematical definition of a hypergraph is an extension to the standard graph concept that allows an edge to point to more than two nodes. * The basic unit of storage in HyperGraphDB is called an atom. Each atom is typed, has an arbitrary value and can point to zero or more other atoms. * Data types are managed by a general, extensible type system embedded itself as a hypergraph structure. Types are themselves atoms as everybody else, but with a particular role (well, as everybody else too). * The storage scheme is platform independent and can thus be accessed by any programming language from any platform. * Size limitations are virtually non-existent. There is no software limit on the size of the graph managed by a HyperGraphDB instance. * The current implementation is solely Java based. It offers an automatic mapping of idiomatic Java types to a HyperGraphDB data schema which makes HyperGraphDB into an object-oriented database suitable for regular business applications. * Embedded in-process: the database comes in the form of a software library to be used directly through its API. * A P2P framework for distributed processing has been implemented for replication/data partitioning algorithms as well as client-server style computing.

* Elastic and linear scalability for a growing data and user base. * Data distribution and replication for performance and fault tolerance. * Multi-datacenter high availability and hot backups. * Support for ACID and eventual consistency. * Support for various storage backends: - Apache Cassandra - Apache HBase - Oracle BerkeleyDB * Support for global graph data analytics, reporting, and ETL * Support for geo, numeric range, and full-text search via ElasticSearch, Solr, and Lucene * Native integration with the TinkerPop graph stack