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bigdata® bigdata® Bigdata® Bigdata® is a horizontally scaled storage and computing fabric supporting optional transactions, very high concurrency, and very high aggregate IO rates. Bigdata® was designed from the ground up as a distributed database architecture running over clusters of 100s to 1000s of machines, but can also run in a high-performance single-server mode.
HyperGraphDB is a general purpose, extensible, portable, distributed, embeddable, open-source data storage mechanism. It is a graph database designed specifically for artificial intelligence and semantic web projects, it can also be used as an embedded object-oriented database for projects of all sizes. The system is reliable and in production use is several projects, including a search engine and our own Seco scripting IDE where most of the runtime environment is automatically saved as a hypergraph. HyperGraphDB - A Graph Database HyperGraphDB - A Graph Database
InfiniteGraph, the Distributed Graph Database InfiniteGraph, the Distributed Graph Database InfiniteGraph enables organizations to achieve greater return on their data related investment by helping them “connect the dots” on a global scale, ask deeper and more complex questions, across new or existing data stores. There is no other graph technology available today, offered by any other commercial vendor or open source project, that can match InfiniteGraph’s combined strengths of persisting and traversing complex relationships requiring multiple hops, across vast and distributed data stores. Download and develop, FREENew: Open-use Talend data connector for InfiniteGraph. Now you can connect your data to InfiniteGraph easily with the tIGOutput.
Introduction aux graphes avec Neo4j et Gephi Les solutions permettant de modéliser, stocker et parcourir de façon efficiente des graphes ont profité de plusieurs éléments qui les ont rendues populaires ces dernières années. Le premier élément aidant à leur démocratisation est l’explosion des réseaux sociaux. Un cas d’usage évident, facile à comprendre même si, étrangement, les solutions mises en œuvre ne sont pas forcément de « type graphe » (par exemple avec FlockDB chez Twitter). Le second est lié au mouvement NoSQL qui a aidé à diffuser l’idée que la base relationnelle n’est pas la seule solution de stockage et de requêtage. Enfin, et même si la théorie des graphes n’est pas neuve, les algorithmes sous-jacents et certaines implémentations ont atteint un niveau de maturité permettant la « commoditisation » de ces technologies, les aidant du même coup à sortir de zones très spécifiques. Introduction aux graphes avec Neo4j et Gephi