Semantics.Datacenter 2.0
Semantics.Datacenter is our newest storage solution based on our proprietary In-Memory Database (IMDB). IMDB provides a scale-out strategy for RDF data storage via the distribution of data and processing over an expandable set of virtual nodes deployed in a cluster on your datacenter hardware. Replication, automatic failover and file-based journaling ensures high availability and recovery of the IMDB storage system.


Clustering allows a data and processing load to be distributed over multiple servers to offer continued growth and scaling. Data and tasks are assigned to virtual nodes without affinity to physical servers. Nodes can be replicated on multiple servers offering load balancing and high availability of data. Virtual nodes are reassigned to available cluster servers automatically upon physical failures.

Partitioned In-Memory Graphs use a patent pending technology designed to optimize RDF storage and querying. They implement a compact indexing scheme to minimize RAM usage while maximizing query performance. IMDB graphs support distributed data partitioning on a cluster that provides a high degree of parallelization of queries and loads. File based journaling ensures proper recovery of graph data in the event of a failure.

Jobs Framework provides highly parallelized processing of data on a cluster. It has a library of built-in data processing tasks that can be assembled into a job using a simple visual workflow interface. In addition, the Jobs Framework allows custom tasks and jobs to be deployed to the cluster.

Integration with Semantics.Server allows the cluster to serve as a write-through cache in front of Semantics.Server or as a read-only mirror of data in Semantic.Server for load balancing.


Semantics.Datacenter is licensing is based on the number of servers used in a single cluster. A server is defined as a single operating system image.

Contact a sales representative at for more information or to purchase licenses.