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Cypher vs SQL](https://image.slidesharecdn.com/neo4jdoc-140915103955-phpapp01/85/Findability-Day-2014-Neo4j-how-graph-data-boost-your-insights-25-320.jpg)
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Findability Day 2014 Neo4j how graph data boost your insights
The document discusses Neo4j, a native graph database. It provides an overview of graph databases and their advantages over traditional SQL databases for connected data. Some key points include: - Graph databases can query relationships between nodes up to 1000x faster than SQL databases as the connectedness of data increases. - Neo4j is built specifically for graph structures, unlike SQL or NoSQL databases. It allows flexible querying of relationships between nodes. - The document outlines several case studies where companies saw improvements like 50x faster calculations and better performance by switching from SQL to Neo4j for applications involving connected user data, knowledge graphs, logistics routing and more.
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Findability Day 2014 Neo4j how graph data boost your insights
- 1. Intro to Neo4j and Graph Databases David Montag Neo Technology ! david@neotechnology.com
- 3. Early Adopters ofGraph Technology
- 4. Survival of theFittest Evolution of Web Search Pre-1999 WWW Indexing Discrete Data 1999 - 2012 Google Invents PageRank Connected Data (Simple) 2012-? Google Knowledge Graph, Facebook Graph Search Connected Data (Rich)
- 5. Survival of theFittest Evolution of Online Recruiting 1999 Keyword Search Discrete Data 2011-12 Social Discovery Connected Data
- 6. Early Adopter Segments (What we expected to happen - view from several years ago) Neo Technology, Inc Confidential Core Industries & Use Cases: Software Financial Services Telecomm-unications Network & Data Center Management Master Data Management Social Geo
- 7. Neo4j Adoption Snapshot Select Commercial Customers* Neo Technology, Inc Confidential Core Industries & Use Cases: *Community Users Not Included Software Financial Services Telecomm-unications Network & Data Center Management Master Data Management Social Geo Finance
- 8. Neo4j Adoption Snapshot Select Commercial Customers* Neo Technology, Inc Confidential Core Industries & Use Cases: Web / ISV Financial Services Telecomm-unications Network & Data Center Management Master Data Management Social Geo Finance Core Industries & Use Cases: Software Financial Services Telecommu nications Health Care & Life Sciences Web Social, HR & Recruiting Media & Publishing Energy, Services, Automotive, Gov’t, Logistics, Education, Gaming, Other Network & Data Center Management MDM / System of Record Social Geo Recommend-ations Identity & Access Mgmt Content Management BI, CRM, Impact Analysis, Fraud Detection, Resource Optimization, etc. Accenture Aviation *Community Users Not Included Finance IT
- 9. What’s a Graph Database?
- 10. Account Customer CUSTOMER_OF Branch balance: $100 ovd_prot: false name: David address: … location: Menlo Park, CA MANAGES Employee name: Mike OWNS CREATED_AT since: 2010
- 11. 143 Alice 326 $100 725 $632 981 $212 143 143 143 326 725 981 Customers Customer_Accounts Accounts
- 12. Alice $100 $632 $212 143 326 725 981 143 981 143 725 143 326
- 13. name: Alice bal:$100 bal: $632 bal: $212 Nodes OWNS OWNS OWNS Relationships
- 14.
- 15. Graph history, benefits & differentiators
- 16.
- 17. bits bits bits bits bits bits bits bits bits bits bits bits bits bits bits bits bits bits bits bits bits bits bits bits bits bits bits bits bits bits
- 21. NoSQL Neo4j Teradata Hadoop Oracle Cassandra MySQL DB2 Sybase Postgres MongoDB RDBMS Analytics Riak Redis Couchbase GigaSpaces Coherence
- 23. Built ground-up forgraphs From the storage layer to the query language, graphs are native to Neo4j. Other NoSQL databases don’t do it at all Relational databases do it very poorly Person Account 326 BofA #1234 John 326 Rigid schema & costly joining of IDs required every lookup mongo
- 24. Connected Query Performance 1000x faster Connectedness of Data Set Response Time RDBMS Degree: < 3 Size: Thousands Neo4j # Hops: 0-1 Degree: Thousands+ Size: Billions+ # Hops: Tens to Hundreds RDBMS vs. Native Graph Database
- 25. (SELECT T.directReportees ASdirectReportees, sum(T.count) AS count FROM ( SELECT manager.pid AS directReportees, 0 AS count FROM person_reportee manager WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") UNION SELECT manager.pid AS directReportees, count(manager.directly_manages) AS count FROM person_reportee manager WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") GROUP BY directReportees UNION SELECT manager.pid AS directReportees, count(reportee.directly_manages) AS count FROM person_reportee manager JOIN person_reportee reportee ON manager.directly_manages = reportee.pid WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") GROUP BY directReportees UNION SELECT manager.pid AS directReportees, count(L2Reportees.directly_manages) AS count FROM person_reportee manager JOIN person_reportee L1Reportees ON manager.directly_manages = L1Reportees.pid JOIN person_reportee L2Reportees ON L1Reportees.directly_manages = L2Reportees.pid WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") GROUP BY directReportees ) AS T GROUP BY directReportees) UNION (SELECT T.directReportees AS directReportees, sum(T.count) AS count FROM ( SELECT manager.directly_manages AS directReportees, 0 AS count FROM person_reportee manager WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") UNION SELECT reportee.pid AS directReportees, count(reportee.directly_manages) AS count FROM person_reportee manager JOIN person_reportee reportee ON manager.directly_manages = reportee.pid WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") GROUP BY directReportees UNION (continued from previous page...) SELECT depth1Reportees.pid AS directReportees, count(depth2Reportees.directly_manages) AS count FROM person_reportee manager JOIN person_reportee L1Reportees ON manager.directly_manages = L1Reportees.pid JOIN person_reportee L2Reportees ON L1Reportees.directly_manages = L2Reportees.pid WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") GROUP BY directReportees ) AS T GROUP BY directReportees) UNION (SELECT T.directReportees AS directReportees, sum(T.count) AS count FROM( SELECT reportee.directly_manages AS directReportees, 0 AS count FROM person_reportee manager JOIN person_reportee reportee ON manager.directly_manages = reportee.pid WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") GROUP BY directReportees UNION SELECT L2Reportees.pid AS directReportees, count(L2Reportees.directly_manages) AS count FROM person_reportee manager JOIN person_reportee L1Reportees ON manager.directly_manages = L1Reportees.pid JOIN person_reportee L2Reportees ON L1Reportees.directly_manages = L2Reportees.pid WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") GROUP BY directReportees ) AS T GROUP BY directReportees) UNION (SELECT L2Reportees.directly_manages AS directReportees, 0 AS count FROM person_reportee manager JOIN person_reportee L1Reportees ON manager.directly_manages = L1Reportees.pid JOIN person_reportee L2Reportees ON L1Reportees.directly_manages = L2Reportees.pid WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") )! MATCH (boss)-‐[:MANAGES*0..3]-‐>(sub), (sub)-‐[:MANAGES*1..3]-‐>(report) WHERE boss.name = “John Doe” RETURN sub.name AS Subordinate, count(report) AS Total Cypher vs SQL
- 26. Forrester estimates thatover 25% of enterprises will be using graph databases by 2017 to support the next-generation applications that need connected data sets. – Forrester Research (TechRadar: Enterprise DBMS, Q1 2014) “ “ … they are the solution that can deliver truly new insights from data. – Svetlana Sicular, Research Director, Gartner
- 27.
- 28. • Support cost& resolution times too high •RDBMS infrastructure did not support expansion – Prem Malhotra, Director Enterprise Architecture “ Neo Technology, Inc Confidential Support Case Support Case Knowledge Base Article Solution Knowledge Base Article Knowledge Base Article Message Support Case Avoidance Challenge Results • Faster answers for customers, with lower reliance on support Relational databases have a hard time dealing with the complexities of connected data.
- 29. MDM / Recommendations • Constructing a 360° view of the customer for the sales team • IBM DB2 system not able to meet performance requirements Neo Technology, Inc Confidential Challenge Results • Flexibly search for insurance policies and associated personal data •Migration and deployment was easy
- 30. Patient transition &referral Challenge Results • Real-time search on Oracle not fast enough for next gen product • Handling 15% of all transitions nationwide in the US • Real-time deep recommendations on widely heterogeneous data Neo Technology, Inc Confidential
- 31. Route Planning •Maintainlarge network of routes covering many carriers and couriers •MySQL-based solution not fast enough for real-time use Neo Technology, Inc Confidential Challenge Results • 50x less code, 2000x faster calculations • Complete ownership of data, and flexibility to modify algorithms
- 32. Real-time Logistics Routing A B 5M Packages Per Day. 3K Per Second. Logistics Solution Model the Logistics Network as a Graph Other examples
- 33. Come talk tous about the graphs you see! Upcoming events: • GotoCon Århus on Sep 29-30 • Øredev Training on Nov 4