AnzoGraph DB Systemeigenschaften

AnzoGraph DB is a massively parallel processing (MPP) native graph database built for diverse data harmonization and analytics at scale (trillions of triples & more), speed and deep link insights. Use it for embedded analytics that requires graph algorithms, graph views, named queries, aggregates, built-in data science functions, data warehouse-style BI and reporting functions.

AnzoGraph DB’s flexible data model and analytical capabilities not only let you load diverse data sets but can perform data warehouse-style analytics, graph algorithms, inferencing and more. It offers a broad set of analytics on a wide range of data, delivered at unparalleled speed and scale. 

Our engine supports labeled properties under the new proposed W3C standard RDF*. Apply properties to vertices and edges for extra analytical firepower. You can intermix RDF and RDF* triples in the same database with no special setup.

Anzograph DB supports geospatial analytics through a partnership with ESRI. We also support virtualization, allowing users to leverage data sets that are not necessarily in the database.

Utilize unique architecture with ultra-fast data loading and super-fast analytical queries, and where performance and data volume capacity handling linearly scale as you add servers. Easily scales to trillions of triples. ACID compliance lets you handle transactions, too.

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Developers can use AnzoGraph DB to build and execute data warehouse-style BI analytics while leveraging our graph algorithms, data science functions and inferencing.

Knowledge Graph - Organizations are using graph databases to build knowledge graphs to provide common business understanding to the data harmonized from diverse sources. Knowledge Graphs stores entities and relationships in data and allows users to search, analyze and use this connected data to accelerate vital new discoveries.

Unstructured Data Analytics - Combined with Natural Language Processing (NLP), graph database offers a free-form repository to store the output of NLP, which is often formatted in RDF triples and use of such data for data discovery and analytics.

AI & Machine Learning - AI and machine learning offer workloads that are well-suited for graph databases. Many of the machine-based algorithms are graph algorithms such as community detection algorithms, pathfinding algorithms, similarity or centrality algorithms.

Anzograph DB has customers in biotech, pharma, financial services and other verticals.

AnzoGraph DB is offered in a free edition, free for commercial use for workloads that use less than 16 GB. Commercial pricing is based primarily on the number of nodes needed to perform workload.