Neo4j GraphDay - Graphs in the Real World: Tope Use Cases for Graph Databases - Rik Van Bruggen, Neo4j
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Rik Van Bruggen welcomed attendees to the Amsterdam graph database event. The agenda included talks on real-world graph use cases, an example use case of securing and auditing Active Directory with Neo4j, and lessons learned from building a scalable platform for sharing 500 million photos. Breakout sessions were scheduled after lunch for introductory training and "GraphClinics".
Neo4j GraphDay - Graphs in the Real World: Tope Use Cases for Graph Databases - Rik Van Bruggen, Neo4j
- 2. Who am I? • Rik Van Bruggen • 5y of graph madness • Lots of blogging, writing, podcasting • Blog.bruggen.com • Learningneo4j.net • Graphistania.com • @rvanbruggen • Don’t forget to #graphday! 2
- 3. Neo4j: The Graph Database Leader 3 2000 2003 2007 2011 2013 2014 20152012 2016 2017 First and only declarative query language for property graph Invented property graph model Extended graph data model to labeled property graph First modern open-source commercial graph DB 1st 1st 1st Introduced 3rd-gen clustering architecture with causal consistency Multi- data center support with network topology awareness 1st First cost-based graph query optimizer 1st Published O’Reilly book on graph DB First native graph DB in 24/7 production First visual development environment for graphs Launched openCypher as “SQL for graphs” standard First database with native graph storage and processing Introduced graph DB as a NoSQL category 1st 1st 1st Scale, performance, governance for global internet apps Security Foundation for data security and compliance V3.2V3.1 1st First built-in graph ETL in Cypher
- 5. Amsterdam, June 6th 2017 09:00 - 9:30 - Welcome Coffee and Registration 9:30 - 9:40 - Welcome by Rik Van Bruggen, Neo4j 09:40 - 10:25 - Graphs in the Real World: Top Use Cases for Graph Databases - Rik Van Bruggen, Neo4j 10:25 - 10:55 - Neo4j example use case: securing and auditing Active Directory - Kees Vegter, Neo4j 10:55 - 11:30 - Break Agenda 5
- 6. Amsterdam, June 6th 2017 11:30 - 12:00 - How Graph Databases drive Enterprises - Darko Krizic, PRODYNA AG 12:00 - 12:20 - Lesson Learned: Building a scalable platform for sharing 500 million photos - Wouter Crooy, Albumprinter 12:20 - 12:30 - Q&A 12:30 - 13:45 - Lunch Agenda 6
- 7. Amsterdam, June 6th 2017 12:30 - 13:45 - Lunch 13:45 - 16:30 - Introductory Training Session 13:45 - 16:30 - GraphClinics Agenda 7
- 8. LET’S START - at the beginning
- 9. WHAT IS A GRAPH?
- 10. A way of representing data DATA DATA
- 11. Relational Database Good for: • Well-understood data structures that don’t change too frequently A way of representing data • Known problems involving discrete parts of the data, or minimal connectivity DATA
- 12. Graph Database Relational Database A way of representing data Good for: • Dynamic systems: where the data topology is difficult to predict • Dynamic requirements: the evolve with the business • Problems where the relationships in data contribute meaning & value Good for: • Well-understood data structures that don’t change too frequently • Known problems involving discrete parts of the data, or minimal connectivity
- 13. THE PROPERTY GRAPH DATA MODEL
- 14. A Graph Is
- 15. A Graph Is
- 16. A Graph Is
- 17. A Graph Is
- 18. A Graph Is
- 20. Use of Graphs has created some of the most successful companies in the world
- 22. Neo4j Use Cases
- 23. NEO4j USE CASES Real Time Recommendations Master Data Management Fraud Detection Identity & Access Management Graph Based Search Network & IT-Operations
- 24. “As the current market leader in graph databases, and with enterprise features for scalability and availability, Neo4j is the right choice to meet our demands.” Marcos Wada Software Developer, Walmart NEO4j USE CASES Real Time Recommendations Master Data Management Fraud Detection Identity & Access Management Graph Based Search Network & IT-Operations
- 25. Neo4j is the heart of Cisco HMP: used for governance and single source of truth and a one-stop shop for all of Cisco’s hierarchies. NEO4j USE CASES Real Time Recommendations Master Data Management Fraud Detection Identity & Access Management Graph Based Search Network & IT-Operations
- 26. “Graph databases offer new methods of uncovering fraud rings and other sophisticated scams with a high-level of accuracy, and are capable of stopping advanced fraud scenarios in real-time.” Large Intelligence Agency Cyber Security Expert NEO4j USE CASES Real Time Recommendations Master Data Management Fraud Detection Identity & Access Management Graph Based Search Network & IT-Operations
- 27. Uses Neo4j to manage the digital assets inside of its next generation in-flight entertainment system. NEO4j USE CASES Real Time Recommendations Master Data Management Fraud Detection Identity & Access Management Graph Based Search Network & IT-Operations
- 28. Uses Neo4j for network topology analysis for big telco service providers NEO4j USE CASES Real Time Recommendations Master Data Management Fraud Detection Identity & Access Management Graph Based Search Network & IT-Operations
- 29. UBS was the recipient of the 2014 Graphie Award for “Best Identify And Access Management App” NEO4j USE CASES Real Time Recommendations Master Data Management Fraud Detection Identity & Access Management Graph Based Search Network & IT-Operations
- 30. Afterglow
- 32. RAFT-based architecture • Continuous availability • Consensus commits Seamless load balancing Drivers à Bolt à Cluster Causal consistency • Tunable ACID-based consistency • Supports “read your own writes” • Best model for graph transactions 1000+ heterogeneous clusters Mix of app servers, large reporting servers, smaller IoT devices Neo4j 3.1 in Review: Causal Clustering: resilient, modern, fault-tolerant architecture 32
- 35. Enterprise Scale for Global Applications Causal Clusters can now span data centers • Clusters can be subdivided into groups and spread across DCs • Read-time choice of consistency at global scale: “Read Any”, “Read-your-own-Writes” Tiered Subclusters boost performance • Speeds local reads and writes • Replica servers pull from nearest replicas minimizing WAN traffic Topology-aware stack insulates developers & apps from the many complexities of clustering Improved Cloud Delivery via RPM, Azure and AWS EC2 35 dc1 group dc2 group
- 37. Groups can include cores or just tiered replicas Hierarchical Replica Server Updates 37 RRRR RR C CORES RRRR C READ REPLICAS RRRR RR RR RR RR RR READ REPLICAS
- 39. Fast, Local Reads and Writes with Global Causal Consistency Across the Cluster Reads occur at the highest speed from a local replica server, which gets refreshed by local cores 39 CORES R R R R R R R R READ REPLICAS R R AnalysisR R READ REPLICAS C CORES RR RR RR RR Analysis RR C C C C READ WRITE Writes are written to a local core server, which propagates the new data to other local cores, and then to remote core servers
- 41. Enterprise Governance Neo4j is IT friendly Node Keys: new type of schema constraint • Tied to labels, nodes can have any number of Node Keys • Ensure graph integrity by enforcing existence and uniqueness • Improves data exchange across multiple data sources Kerberos encrypted-authentication module add-on • Supports three-tier integration of client, directory and database Causal Clustering available on CAPI-Flash hardware from IBM Power8 via add-on Better metrics in Query Monitor to reveal query behavior and resource consumption 41
- 42. Native Graph Performance Improvements • Native Label index improves write speed by 30- 300% • Composite indexes supercharge lookup speeds • Cypher’s depth query in DISTINCT function eliminates repetitious traversals through deep levels creating exponential time savings • New Compiled Cypher runtime in Enterprise Edition to speed common queries by 300% • Cost-based-optimizer replaces rules based optimizer (which has been deprecated) • Snappier Neo4j Browser with new more flexible JavaScript framework 42
- 44. Amsterdam, June 6th 2017 09:00 - 9:30 - Welcome Coffee and Registration 9:30 - 9:40 - Welcome by Rik Van Bruggen, Neo4j 09:40 - 10:25 - Graphs in the Real World: Top Use Cases for Graph Databases - Rik Van Bruggen, Neo4j 10:25 - 10:55 - Neo4j example use case: securing and auditing Active Directory - Kees Vegter, Neo4j 10:55 - 11:30 - Break Agenda 44
- 45. THANK YOU!