InfiniteGraph is an enterprise distributed graph database that's scalable and can perform real-time searches for large organizations with massive amounts of complex, interconnected data in multiple locations. It adds value to analytics applications by using graph algorithms to discover and store connections and relationships.
For applications that rely on relationships between and among data, InfiniteGraph can exploit distributed data using flexible and configurable storage locations. It can also efficiently distribute the processing load for applications.
The primary component of InfiniteGraph is a set of database libraries that are embedded into client applications. These allow the application to store and query graph objects in the database. A set of database administration tools is also provided to manage the graph database in a distributed environment.
InfiniteGraph offers flexible consistency models, from ACID (Atomicity, Consistency, Isolation and Durability) to eventually consistent.
InfiniteGraph distributed graph database features
InfiniteGraph 3.3 and 3.4 include the following:
- Drastic performance improvements (compared with previous versions) for data ingest operations and for operations that delete vertices and edges.
- New methods that provide improved functionality for edge, vertex and hop discovery.
- Enhanced navigation query and database-wide, high-performance batch query capabilities.
- Updated SLF4J logging, which enables the user to customize log output.
- Updated Tinkerpop Blueprints, which consist of a collection of interfaces, implementations and test suites for the property graph data model. Blueprints is somewhat analogous to Java Database Connectivity, but for graph databases.
- Critical bug fixes.
InfiniteGraph can be used to build data-intensive, graph-based applications rapidly using an API that natively supports the concepts of vertices and edges. It offers flexible annotation available for edges, which are -class objects.
Additionally, InfiniteGraph's configurable, model-based technique for placing elements in a graph database enables managed placement for quick, out-of-the-box usage. Or you can create a custom model to physically collocate graph elements that are often accessed together to enhance navigation query performance. You can also physically separate or isolate frequently accessed data objects to avoid lock contention.
The InfiniteGraph distributed graph database runs on Mac OSx, Linux and Windows operating systems.
Licensing terms for InfiniteGraph
InfiniteGraph is sold by Objectivity Inc. and its partners and is generally priced by the number of cores per server or through a royalty model that's either a percentage of revenue or a unit fee. InfiniteGraph offers volume discounts as well as a GSA schedule. A free 60-day trial of the full version is available for download.
Standard support, which includes email and phone troubleshooting and upgrades to the latest releases, is offered annually for typically 18% of the license fees. Custom and 24/7 support are available for an additional annual fee.
Although there are no standard distributed graph database benchmarks, Objectivity can provide performance metrics by request.
About the author
Craig S. Mullins is a data management strategist, researcher, consultant and author with more than 30 years of experience in all facets of database systems development. He is president and principal consultant of Mullins Consulting Inc. and publisher/editor of TheDatabaseSite.com. Email him at firstname.lastname@example.org. Email us at email@example.com and follow us on Twitter: @sDataManagement.
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