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Graph Processing with Titan and Scylla


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Graphs are growing in popularity, but the landscape is becoming a hairball. Learn how to unravel it with the Apache TinkerPop graph computing framework and Gremlin, a functional, data flow language for traversing graphs. This session helps you distinguish between OLTP and OLAP graph processing as well as how to bridge the gap between graph databases and graph engines. We will talk specifically about how Titan, an open source graph database, can combine with Scylla to handle both types of workloads.

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Graph Processing with Titan and Scylla

  1. 1. Graph Processing with Titan and Scylla Jason Plurad Software Engineer, IBM Open Technology PMC and Committer, Apache TinkerPop
  2. 2. Graphs with Titan and Scylla ØGraph computing • Graph landscape • Titan and Scylla
  3. 3. Common graph data domains • Social network analysis • Configuration management database • Master data management • Recommendation engines • Knowledge graphs • Internet of things
  4. 4. Apache TinkerPop: Graph Computing Framework
  5. 5. Property graph and Gremlin • Structure § Vertex § Edge § Properties • Gremlin § Domain specific language (DSL) for graph § Functional, data flow approach § Full library of traversal steps § Support for non-JVM languages
  6. 6. Graphs with Titan and Scylla üGraph computing ØGraph landscape • Titan and Scylla
  7. 7. Graph Landscape • Graph database vs Graph processor § OLTP vs OLAP § Neighborhood vs Whole graph
  8. 8. Apache Spark or Apache Giraph • Pick a graph processor for OLAP… § Spark is the new hotness in analytics § Giraph is better suited for gigantic graphs • By using Apache TinkerPop and Gremlin, we can use either one seamlessly
  9. 9. Titan (Aurelius) • Pick a graph database for OLTP… • Pluggable storage backend • Pluggable indexing backend • Gift from Matthias Broecheler and Dan LaRocque • Apache license but not in ASF?
  10. 10. DataStax Enterprise Graph? • Apache TinkerPop compliant • Not open source • Titan inspired • Gremlin tooling with DataStax Studio
  11. 11. Graphs with Titan and Scylla üGraph computing üGraph landscape ØTitan and Scylla
  12. 12. Why Titan? • Designed for big graphs (10B+ edges) • Local graph traversals (OLTP) • Batch graph processing (OLAP) • Desire a free, open source distributed graph database
  13. 13. Titan Key Features • Data management • Vertex-centric indices • Graph partitioning • Edge compression
  14. 14. Titan Architecture
  15. 15. Why Scylla? • Drop-in replacement for Cassandra 2.1.8 • Thrift support (Duarte Nunes) § Partial support in 1.3 § Full support in 1.4 • Titan is compatible with Scylla 1.3 § OLTP with Scylla is crazy fast § OLAP via SparkGraphComputer
  16. 16. Titan reawakened with Scylla • Next steps • Benchmarking OLTP and OLAP with Scylla • Transition Titan to native CQL § Essentially a rewrite § Materialized views • Native search in Scylla?
  17. 17. • Open source leads the way • Partner with open communities
  18. 18. Thank You! Twitter/GitHub @pluradj