We originally commissioned this workshop for recent Graph Day conference held in Austin, January 2017. The workshop sold out and received rave reviews. We have asked Josh Perryman, of Expero, to offer it again.

There is currently no other course like this - anywhere in the world.

We are presenting this hands-on Introduction to the TinkerPop/Gremlin as part of the upcoming Graph Day Conference in San Francisco, . As far as we know, this is currently the only TinkerPop / Gremlin training workshop in the world.

There will only be one section of this class, and enrollment is limited to 30. Don't miss this opportunity!

Apache TinkerPop™ is an open source, vendor-agnostic, graph computing framework distributed under the commercial friendly Apache2 license. When a data system is TinkerPop-enabled, its users are able to model their domain as a graph and analyze that graph using the Gremlin graph traversal language. Furthermore, all TinkerPop-enabled systems integrate with one another allowing them to easily expand their offerings as well as allowing users to choose the appropriate graph technology for their application. Sometimes an application is best served by an in-memory, transactional graph database. Sometimes a multi-machine distributed graph database will do the job. Or perhaps the application requires both a distributed graph database for real-time queries and, in parallel, a Big(Graph)Data processor for batch analytics. Whatever the application's requirements, there exists a TinkerPop-enabled graph system out there to meet its needs.

Gremlin is an incredibly rich and powerful query language for property graphs. Its functional roots and novel execution model can make it a little difficult to get started with; many instincts from set-based query languages like SQL don't translate directly. In this 3 hour workshop, led by Gremlin expert Josh Perryman, you will work through a series of increasingly complex exercises.

About the instructor

Josh Perryman likes to play with data. Oftentimes this is implementing proprietary algorithms closer to the data for performance or scale. Sometimes it is ad-hoc investigation and analysis, a sort of exploratory querying. A few times he’s been able to leverage his experience with data engines for dramatic performance improvements. But the real joy is designing a schema for both functionality and performance, one which increases the productivity of other developers and enables a technology to solve new problems or deliver new value to the business. But technology isn't just data, and he does more than just play with data. He’s worked with high performance computing (HPC) environments, taking computations from hours to minutes or seconds. He has built visualizations which deliver new insights into complex data domains. He’s managed technology personnel, both directly and indirectly, to deliver technology solutions. He’s have put together more types of technology components, software and hardware, than can be counted, because one of his fortes is solving problems by building sustainable systems.