SYSTAP Wins 2015 Big Data Startup Award at Big Data Innovation Summit

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The Innovation Enterprise has just announced winners for the 2015 Big Data Innovation Awards in San Jose, and SYSTAP™ is honored to receive the award for Big Data Startup. SYSTAP won this award for its Blazegraph™ and MapGraph™ technologies for graph analytics at scale.

Systap CEO Brad Bebee upon winning the 2015 Big Data Startup Award at Big Data Innovation Summit

Systap software products solve problems that require crunching phenomenal amounts of data, ranging from embedded-graph databases to 1+ trillion edge scale-out architectures, to GPU-accelerated graph analytics traversing billions of edges in milliseconds.

Technology firm SYSTAP™ wins with its game-changing technology for graphs at scale. The Innovation Enterprise has just announced winners for the 2015 Big Data Innovation Awards in San Jose, and SYSTAP is honored to receive the award for Big Data Startup. SYSTAP won this award for its Blazegraph™ and MapGraph™ technologies for graph analytics at scale.

“It’s great to be recognized with this Big Data Innovation Award. Our products accelerate how we process massive amounts of data using graph functionality. This allows us to address very challenging problems that require crunching phenomenal amounts of data. We are delivering software products ranging from embedded-graph databases to 1+ trillion edge scale-out architectures, to GPU-accelerated graph analytics traversing billions of edges in milliseconds,” says Brad Bebee, CEO, SYSTAP.

Why are super-fast graphing technologies important? In today’s always-on and always-connected world, the amount of data that people generate every second is huge and is growing at an incredible rate. Graphs are a way to organize this information by linking it together.

Graphs occur in many important domains and markets. A social network of people and their connections, a fraud-detection system, a battlefield filled with soldiers and other resources, or a human body made of many biological systems are all examples of graphs. The potential of graph analytics is well known, but existing platforms have been limited in their ability to process this information at a large scale. The next generation of significant business, medical, and information science advances will be made by those who can harness the data and its links quickly and cost-effectively, drawing new conclusions and making discoveries at lightning speed. Graph technology can be used to find cures for diseases such as cancer by helping researchers find patterns that are otherwise impossible to detect.

Why is it hard to scale graphs? Scaling graphs is hard because they are not like other big data challenges. As you scale up, graphs become billion edge structures that challenge current architectures. The reason why computers struggle to process this quantity of graph data is because memory bandwidth is slow in CPU architectures. The leading work is improving CPU main memory processing for graph-parallel applications. While CPU cores are fast, the non-locality of graph data means that slow memory bandwidth causes CPUs to wait. SYSTAP calls this the “Graph Cache Thrash.” Getting to scale with large graphs means choosing the right hardware and software architecture.

For SYSTAP, graph scaling is the opportunity. They have discovered a way to exploit the memory bandwidth of GPUs to provide extreme scaling that is hundreds of times faster and 40 times more affordable; 10,000 times faster than disk-based. They developed a leading Graph Database platform, Blazegraph, that provides High Availability and Scale-Out Architectures.

Blazegraph enables customers to achieve graphs at scale across business needs from embedded databases to low-latency near-realtime large graphs to high availability and trillion edge graphs with good query performance. SYSTAP’s technology makes GPU accessible for graphs with a Vertex-Centric API. It uses partitioning and overlapping communications to achieve very large scale: it traverses billions of edges in milliseconds. The early research was funded by DARPA and co-developed with the University of Utah SCI institute. Its pedigree is in HPC systems running on over 750-M Cores on the TITAN Super Computer.

“Facebook is currently more than a trillion edges and we believe it takes more than 10 minutes using 200+ racks of servers to traverse their graph over a single iteration. We believe our GPU acceleration technology could do it in seconds on a cluster of GPUs with similar RAM,” says Brad Bebee, CEO, SYSTAP.

What are the technologies that were recognized in the award? Blazegraph is an ultra high-performance graph database supporting Blueprints and RDF/SPARQL APIs. It supports up to 50 Billion edges on a single machine and has a High Availability and Scale-out architecture. It is in production use for Fortune 500 customers such as EMC, Autodesk, and many others. The Wikimedia Foundation recently chose Blazegraph to power the Wikidata Query Service.

Released in 2015, Mapgraph Accelerator™ is a disruptive new technology using GPUs to accelerate data-parallel graph analytics up to 10,000 times faster than other approaches. It can traverse billions of edges in milliseconds. It is a GPU-based plug-in to SYSTAP’s industry leading, open-source graph database platform, Blazegraph. Mapgraph Accelerator marries the speed of GPUs with familiar Java APIs and standardized query languages. It will provide the world’s first and best platform for building graph applications with GPU-acceleration. It will bridge the gap between the Blazegraph database platform and the GPU acceleration for graph analytics. Users of the Blazegraph platform will be able to leverage GPU-accelerated graph analytics via a Java Native Interface (JNI) and via predicates in SPARQL query.

Mapgraph HPC™ is the application of the technology to GPU clusters where it can traverse 100 billion edge graphs in sub-second times. The HPC product provides GPU acceleration for very large graphs using clusters of GPUs. The standard measure of graph performance is a GTEP; 1 Billion Traversed Edges Per Second. Mapgraph HPC today has a 10 times advantage over super-computer solutions. The Pascal architecture will make that 40 times in 2016. Partnering with domain analytic providers and developing SaaS Analytics for graph analytics on-demand will further broaden the market and democratize the capabilities for graphs at scale.

Whether customers need an embedded graph database, a 1 Trillion Edge Graph Database, or the ability to traverse billions of edges in milliseconds, SYSTAP’s award-winning graph solutions are built to surpass their needs.

For more information about the 2015 Big Data Innovations Summit, please visit https://theinnovationenterprise.com/summits/big-data-innovation-summit-san-jose

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About Systap:
SYSTAP, LLC is a software company focused on Big Graphs with open source and commercial software solutions. Its first product, Blazegraph, is an ultra high-performance graph database. Its new products, MapGraph Accelerator and MapGraph HPC, use the new disruptive technology of GPUs to accelerate data-parallel graph analytics.

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Brad Bebee
Systap
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