Bloor Research & DataStax: How graph databases solve previously unsolvable business and technology challenges
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This webinar covered graph databases and how they can solve problems that were previously difficult for traditional databases. It included presentations on why graph databases are useful, common use cases like recommendations and network analysis, different types of graph databases, and a demonstration of the DataStax Enterprise graph database. There was also a question and answer session where attendees could ask about graph databases and DataStax Enterprise graph.
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Bloor Research & DataStax: How graph databases solve previously unsolvable business and technology challenges
- 1. Webinar | Bloor Research & DataStax : How graph databases solve previously unsolvable business and technology challenges December 8th 2016 Philip Howard, Research Director, Bloor Research International Jonathan Lacefield, Product Manager, DataStax
- 2. 1 Welcome & Introductions, Andrea Cross, DataStax 2 Graph Databases: Why & Which? Philip Howard, Bloor Research International 3 Fireside Chat, Philip Howard & Jonathan Lacefield 4 DataStax Enterprise Graph, Jonathan Lacefield, DataStax 5 Q & A Wrap Up, Andrea Cross 2© DataStax, All Rights Reserved.
- 3. telling the right storyConfidential © Bloor Research 2016 Graph databases: why and which? Philip Howard Research Director
- 4. telling the right storyConfidential © Bloor Research 2016 • Do you have a graph problem? • Use cases • Types of graph database Agenda
- 5. telling the right storyConfidential © Bloor Research 2016 What is a graph? Not this This
- 6. telling the right storyConfidential © Bloor Research 2016 Why not relational? When it’s less about the data and more about the relationships
- 7. telling the right storyConfidential © Bloor Research 2016 Problems with complexity BoM: Trunnion mounted ball valves
- 8. telling the right storyConfidential © Bloor Research 2016 => poor performance/scale Multiple self joins are often an issue
- 9. telling the right storyConfidential © Bloor Research 2016 Use case 1: multiple self joins A fraud ring: an example of network analysis – there are lots of other such use cases
- 10. telling the right storyConfidential © Bloor Research 2016 Use case 2: MDM and Customer 360º
- 11. telling the right storyConfidential © Bloor Research 2016 Use case 3: recommendations Products, dates, hotels, movies.
- 12. telling the right storyConfidential © Bloor Research 2016 Use case 4: research
- 13. telling the right storyConfidential © Bloor Research 2016 Use case 5: PageRank Many other graph algorithms
- 14. telling the right storyConfidential © Bloor Research 2016 Use case 6: text analysis
- 15. telling the right storyConfidential © Bloor Research 2016 Use case 7: data unification
- 16. telling the right storyConfidential © Bloor Research 2016 • Two fundamental types: • Property graphs • RDF (resource description framework) Graphs • Distinction is often not clear-cut • Native versus non-native databases • Implementation specific • Multi-model databases • Implementation specific Types of graph database
- 17. telling the right storyConfidential © Bloor Research 2016 • Text processing/semantics • Search engines, sometimes ontologies • Sometimes text mining • Reasoning functions (OWL) • Typically query the graph • Oblivious to data (un)structure • SPARQL query language • Tend to be used for complex analytics (but all graph databases support analytics) RDF databases
- 18. telling the right storyConfidential © Bloor Research 2016 • Typically as replacements for rdbms where relational technology cannot perform • Good for MDM, Recommendations, Network analytics, Customer 360º… • Starting point is structured data but unstructured also • Traverse the graph rather than query it • Use Gremlin, Apache Tinkerpop and/or proprietary versions of (extended) SQL Property graphs
- 19. telling the right storyConfidential © Bloor Research 2016 • Two specialised variants: • Graph “compute” engines for complex analytics and cognitive computing • Unification graph databases • Specialised niches • E.g. Cybersecurity Other options
- 20. telling the right storyConfidential © Bloor Research 2016 Further resources See: www.bloorresearch.com/technology/graph-databases/
- 21. Fireside Chat Jonathan Lacefield, DataStax Philip Howard, Bloor Research
- 23. Founded in April 2010 500+ Santa Clara, San Francisco, Austin, London, Paris, Berlin, Tokyo, Sydney 400+ Employees Customers 30+ Percent Overview Ranked #1 in multiple operational database categories
- 24. 24 © DataStax, All Rights Reserved. DataStax Enterprise (DSE) The database for cloud applications
- 25. • Make sense of complex, seemingly unconnected data • Scale-out graph database • Built on Apache TinkerPopTM • Build quickly, with a consistent skill set • Graph support within DSE • Engineered for Apache CassandraTM • Part of DSE’s multi-model platform • Achieve instant insight • Real-time search and analytic queries © DataStax, All Rights Reserved. DSE Graph – Scale Out Power for Graph
- 26. © DataStax, All Rights Reserved. Expero uses DSE Graph to manage role-based asset access to improve efficiency and compliance.
- 27. Q&A
- 28. Contacts & Resources ● Download DSE Graph http://www.datastax.com/products/datastax-enterprise-graph ● Read the Documentation http://docs.datastax.com/en/latest-dse/datastax_enterprise/graph/graphTOC.html ● Take DataStax Academy Training DS330 – DataStax Graph https://academy.datastax.com/courses/ds330-datastax-enterprise-graph ● Join the DataStax Professionals Community Conversation https://academy.datastax.com/slack linkedin.com/company/datastax linkedin.com/in/jlacefield linkedin.com/in/philip-howard-08a763 @BloorResearch @jlacefie @DataStax © 2015 DataStax, All Rights Reserved. 28
- 29. THANK YOU! © 2015 DataStax, All Rights Reserved. 29