SYSTAP, LLC was founded in 2006 with vision of building high quality, highly scalable, open-source software solutions for big graphs. While graph problems may look similar to other big data challenges from the outside, they have very different computational workloads and scaling requirements. Techniques that work on a small scale will often fail to deliver on larger graphs. SYSTAP’s solutions fill the gap created by this “big graph anti-pattern”. We believe the only way to get scaling and high throughput for graph traversal and graph mining is to get the architecture, the software, and the hardware right. Helping customers achieve their business objectives with graph data is our vision, mission, and the essence of our software solutions.

SYSTAP’s flagship product, Blazegraph, has been a market leader since 2006 in providing high performance, scalable solutions for graphs. It is built on the same platform and maintains 100% binary and API compatibility with Bigdata®. The Blazegraph platform supports both Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop, blueprints, vertex-centric) APIs. It features robust, scalable, fault-tolerant, enterprise-class storage and query and high-availability with online backup, failover and self-healing. Blazegraph powers many high profile enterprise applications for customers including EMC, AutoDesk, and Yahoo!7. Learn more at http://systap.com.

MapGraph™ Accelerator (Beta) provides GPU-Accelerated Graph Analytics for Blazegraph. It is a plug-in capability for Blazegraph™ to provide single-GPU graph analytics using a Java API.

SYSTAP’s MapGraph HPC is a new and disruptive technology for organizations that need to process large graphs in near-real time. It cost effectively brings the capabilities of High Performance Computing (HPC) to your organization’s biggest and most time critical graph challenges. MapGraph provides a familiar vertex-centric graph programming model, but its GPU acceleration is 100s of times faster than competing CPU-only technologies and up to 100,000 times faster than graph technologies based on key-value stores such as HBase, Titan, and Accumulo. MapGraph runs on one GPU or a cluster of GPUs. With MapGraph on 64 NVIDIA K40 GPUs, you can traverse a scale-free graph of 4.3 billion directed edges in .15 seconds for a throughput of 32 Billion Traversed Edges Per Second (32 GTEPS). Learn more at http://MapGraph.io.