MapGraph -- the GPU-accelerated graph engine -- has been rolled into Blazegraph 2.0, and it looks like this means OLTP and OLAP can be combined into a blazing-fast, single OLXP system.<p>From: <a href="https:&#x2F;&#x2F;www.blazegraph.com&#x2F;product&#x2F;gpu-accelerated&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.blazegraph.com&#x2F;product&#x2F;gpu-accelerated&#x2F;</a><p><pre><code>  The original work was funded by DARPA and presented at the 
  2014 SIGMOD conference in a paper entitled, MapGraph: A 
  High Level API for Graphs [1]. This work is available in 
  open source. Later work, in collaboration with the 
  University of Utah SCI Institute [2] and funded by DARPA, 
  applied multi-core techniques running on over 750 M cores 
  on the Titan Supercomputer to extend this to Multi-GPU 
  traversal with Breadth First Search (BFS).  On a cluster of 
  64 NVIDIA K40 GPUs, it demonstrated a throughput of 32 
  Billion Traversed Edges Per Second (32 GTEPS), traversing a 
  scale-free graph of 4.3 billion directed edges in 0.15 
  seconds, which was featured in a presentation IEEE Bigdata 
  Conference.
</code></pre>
[1] <a href="https:&#x2F;&#x2F;www.blazegraph.com&#x2F;whitepapers&#x2F;MapGraph-SIGMOD-2014.pdf" rel="nofollow">https:&#x2F;&#x2F;www.blazegraph.com&#x2F;whitepapers&#x2F;MapGraph-SIGMOD-2014....</a><p>[2] <a href="http:&#x2F;&#x2F;www.sci.utah.edu&#x2F;publications&#x2F;Fu2014a&#x2F;UUSCI-2014-002.pdf" rel="nofollow">http:&#x2F;&#x2F;www.sci.utah.edu&#x2F;publications&#x2F;Fu2014a&#x2F;UUSCI-2014-002....</a><p>VIDEO: Blazegraph GPU and DASL at Super Computing 2015 (<a href="https:&#x2F;&#x2F;vimeo.com&#x2F;148519808" rel="nofollow">https:&#x2F;&#x2F;vimeo.com&#x2F;148519808</a>)<p>It&#x27;s GPLv2 and now has support for SPARQL and TinkePop3&#x2F;Gremlin.<p>See <a href="https:&#x2F;&#x2F;groups.google.com&#x2F;d&#x2F;topic&#x2F;gremlin-users&#x2F;8fS_ak-tWNs&#x2F;discussion" rel="nofollow">https:&#x2F;&#x2F;groups.google.com&#x2F;d&#x2F;topic&#x2F;gremlin-users&#x2F;8fS_ak-tWNs&#x2F;...</a>