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GraphTour - Neo4j Platform Overview

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Neo4j GraphTour Europe 2019

Publié dans : Logiciels
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GraphTour - Neo4j Platform Overview

  1. 1. Neo4j Platform Overview Ivan Zoratti Director of Product Management - Neo4j Database
  2. 2. What Is Different In Neo4j?
  3. 3. What Is Different In Neo4j? 3 TRADITIONAL DATABASES Store and retrieve data Real time storage & retrieval Up to 3 Max # of hops
  4. 4. What Is Different In Neo4j? 4 TRADITIONAL DATABASES BIG DATA TECHNOLOGY Store and retrieve data Aggregate and filter data Real time storage & retrieval Long running queries Aggregation & filtering Up to 3 Max # of hops 1
  5. 5. What Is Different In Neo4j? 5 TRADITIONAL DATABASES BIG DATA TECHNOLOGY Store and retrieve data Aggregate and filter data Connections in data Real time storage & retrieval Real-Time Connected Insights Long running queries Aggregation & filtering “Our Neo4j solution is literally thousands of times faster than the prior MySQL solution, with queries that require 10-100 times less code” Volker Pacher, Senior Developer Up to 3 Max # of hops 1 Millions
  6. 6. What Is Different In Neo4j? Index-Free Adjacency 6
  7. 7. What Is Different In Neo4j? Minutes to Milliseconds Real-time Query Performance 7 Index-free Connectedness and Size of Data Set ResponseTime Relational and Other NoSQL Databases 0 to 2 hops 0 to 3 degrees Thousands of connections 1000x Advantage Tens to hundreds of hops Thousands of degrees Billions of connections Neo4j “Minutes to milliseconds”
  8. 8. What Is Different In Neo4j? ACID Graph Writes: A Requirement for Graph Transactions 8 Graph Transactions Over ACID Consistency Graph Transactions Over Non Graph-ACID DBMSs Maintains Integrity Over Time Guaranteed Graph Consistency Becomes Corrupt Over Time Not Good Enough for Graphs
  9. 9. What Is Different In Neo4j? Cypher Query Language 9 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 Project Impact Less time writing queries • More time understanding the answers • Leaving time to ask the next question Less time debugging queries: • More time writing the next piece of code • Improved quality of overall code base Code that’s easier to read: • Faster ramp-up for new project members • Improved maintainability & troubleshooting
  10. 10. The DBMS Market: Evolutionary Timeline 10 Data Storage & Retrieval for specific use cases Data Storage & Retrieval for all new use cases Connected Data for specific use cases Connected Data for all new use cases Codd’s Paper 2010 Neo4j v1.0 1979 1990 2025 Oracle IPO 1986 2019 openCypher Launch Relational Key-Value Column Family Document Graph
  11. 11. Enabling the Connected Enterprise 11 Transactional Graphs Graph Visualization • Fraud detection • Real-time recommendations • Network and IT operations management • Knowledge graphs • Master data management • Fraud detection • Network and IT operations management • Product information management • Risk and portfolio analysis AI & Graph Analytics • Sentiment analysis • Customer segmentation • Machine learning • Cognitive computing • Community detection Data Scientists Business Users Applications
  12. 12. Neo4j Graph Platform 12 Development & Administration Analytics Tooling BUSINESS USERS DEVELOPERS ADMINS Graph Analytics Graph Transactions Data Integration Discovery & Visualization DATA ANALYSTS DATA SCIENTISTS Drivers & APIs APPLICATIONS AI openCypherCloud
  13. 13. Enterprise Maturity & Robustness 13 Neo4j Security Foundation Multi-Clustering Support for Global Internet Apps Rolling Upgrades Schema Constraints Concurrent/Transactional Write Performance Auto Cache Reheating For Restarts, Restores and Cluster Expansion Neo4j 3.4 now supports rolling upgrades 3.4 3.5 Upgrade older instances while keeping other members stable and without requiring a restart of the environment 3.5
  14. 14. 14 Development & Administration Analytics Tooling Graph Analytics Graph Transactions Data Integration Discovery & VisualizationDrivers & APIs AI Neo4j Graph Platform: Where We Are Today
  15. 15. 15 Development & Administration Analytics Tooling Graph Analytics Graph Transactions Data Integration Discovery & VisualizationDrivers & APIs AI Improved Admin Experience - Rolling upgrades - Brute force attack prevention - Fast, resumable backups - Cache Warming on startup - Improved diagnostics Neo4j Graph Platform: Where We Are Today
  16. 16. 16 Development & Administration Analytics Tooling Graph Analytics Graph Transactions Data Integration Discovery & VisualizationDrivers & APIs AI Improved Admin Experience - Rolling upgrades - Brute force attack prevention - Fast, resumable backups - Cache Warming on startup - Improved diagnostics Multi-Cluster routing built into Bolt drivers Seabolt & Go Driver - Other v1.7 Supported Drivers: Java, JavaScript, Python, .NET - Community Drivers: Perl, PhP, Ruby, Erlang, R, Haskell, Clojure, JDBC and many others Neo4j Graph Platform: Where We Are Today
  17. 17. 17 Development & Administration Analytics Tooling Graph Analytics Graph Transactions Data Integration Discovery & VisualizationDrivers & APIs AI Improved Admin Experience - Rolling upgrades - Brute force attack prevention - Fast, resumable backups - Cache Warming on startup - Improved diagnostics Multi-Cluster routing built into Bolt drivers Seabolt & Go Driver - Other v1.7 Supported Drivers: Java, JavaScript, Python, .NET - Community Drivers: Perl, PhP, Ruby, Erlang, R, Haskell, Clojure, JDBC and many others Neo4j Bloom - New graph illustration and communication tool for non-technical users - Explore and edit graph - Search-based - Create storyboards - Foundation for graph data discovery - Integrated with graph platform Neo4j Graph Platform: Where We Are Today
  18. 18. 18 Development & Administration Analytics Tooling Graph Analytics Graph Transactions Data Integration Discovery & VisualizationDrivers & APIs AI Improved Admin Experience - Rolling upgrades - Brute force attack prevention - Fast, resumable backups - Cache Warming on startup - Improved diagnostics Multi-Cluster routing built into Bolt drivers Seabolt & Go Driver - Other v1.7 Supported Drivers: Java, JavaScript, Python, .NET - Community Drivers: Perl, PhP, Ruby, Erlang, R, Haskell, Clojure, JDBC and many others Neo4j Bloom - New graph illustration and communication tool for non-technical users - Explore and edit graph - Search-based - Create storyboards - Foundation for graph data discovery - Integrated with graph platform Graph Data Science High speed graph algorithms Neo4j Graph Platform: Where We Are Today
  19. 19. 19 Development & Administration Analytics Tooling Graph Analytics Graph Transactions Data Integration Discovery & VisualizationDrivers & APIs AI Improved Admin Experience - Rolling upgrades - Brute force attack prevention - Fast, resumable backups - Cache Warming on startup - Improved diagnostics Multi-Cluster routing built into Bolt drivers Seabolt & Go Driver - Other v1.7 Supported Drivers: Java, JavaScript, Python, .NET - Community Drivers: Perl, PhP, Ruby, Erlang, R, Haskell, Clojure, JDBC and many others Neo4j Bloom - New graph illustration and communication tool for non-technical users - Explore and edit graph - Search-based - Create storyboards - Foundation for graph data discovery - Integrated with graph platform Graph Data Science High speed graph algorithms Neo4j Database 3.4 & 3.5 - 70% faster Cypher - Native GraphB+Tree Indexes (up to 5x faster writes) - Full-text search - Index-Backed Optimisation - 100B+ bulk importer - Date/Time data type - 3-D Geospatial search - Secure, Horizontal Multi-Clustering - Property Blacklisting - Causal Cluster with Raft v2 Protocol - Hostname verification, Intra-cluster discovery encryption Neo4j Graph Platform: Where We Are Today
  20. 20. Neo4j Graph Platform: Where We Are Today 20 Development & Administration Analytics Tooling Graph Analytics Graph Transactions Data Integration Discovery & VisualizationDrivers & APIs AI Improved Admin Experience - Rolling upgrades - Brute force attack prevention - Fast, resumable backups - Cache Warming on startup - Improved diagnostics Multi-Cluster routing built into Bolt drivers Seabolt & Go Driver - Other v1.7 Supported Drivers: Java, JavaScript, Python, .NET - Community Drivers: Perl, PhP, Ruby, Erlang, R, Haskell, Clojure, JDBC and many others SparkCypher/Morpheus (pre-EAP) Spark Implementation Proposal for getting Cypher into Spark Neo4j Bloom - New graph illustration and communication tool for non-technical users - Explore and edit graph - Search-based - Create storyboards - Foundation for graph data discovery - Integrated with graph platform Graph Data Science High speed graph algorithms Neo4j Database 3.4 & 3.5 - 70% faster Cypher - Native GraphB+Tree Indexes (up to 5x faster writes) - Full-text search - Index-Backed Optimisation - 100B+ bulk importer - Date/Time data type - 3-D Geospatial search - Secure, Horizontal Multi-Clustering - Property Blacklisting - Causal Cluster with Raft v2 Protocol - Hostname verification, Intra-cluster discovery encryption
  21. 21. Graph Visualization Options for Neo4j 21 Neo4j Bloom - Provided by Neo4j - Exclusively optimized for Neo4j graphs - Deploys easily in Neo4j Desktop - Focused on graph exploration thru a code-free UI - Near natural language search - Currently caters to data analysts and graph SMEs - Currently for individual or small team use Viz Toolkits - 3rd party e.g. vis.js, d3.js, Keylines - Some offer data hooks into Neo4j, others may require custom integration - Offer robust APIs for flexible control of the viz output - Cater to developers who will create a custom solution, usually with limited interactivity - Departmental, enterprise or public use BI Tools - 3rd party e.g. Tableau, Qlik - Not optimized for graph data, may require a special connector - UI for dashboard and report creation with many kinds of viz, in addition to graph viz - Cater to business users and data analysts - Departmental, cross- department or enterprise use Graph Viz Solutions - 3rd party e.g. Linkurious, Tom Sawyer - Have to support multiple graph models and sources - Feature UI for exploration or APIs for customizing output and embedding/publishing - Solutions may cater to business users, analysts or developers - Small team, departmental or cross-department use Little Technical Expertise Most Technically Involved Exploration Focus Publishing/Consumption Focus Smaller Deployments Larger Deployments
  22. 22. Neo4j Bloom 22
  23. 23. Neo4j Bloom 23 Perspective Business view of the graph Departmental views • Hiding PII • Styling
  24. 24. Neo4j Bloom 24 Perspective Business view of the graph Departmental views • Hiding PII • Styling Visualization GPU Accelerated Visualization High performance physics & rendering
  25. 25. Neo4j Bloom 25 Perspective Business view of the graph Departmental views • Hiding PII • Styling Visualization GPU Accelerated Visualization High performance physics & rendering Exploration Direct graph interactions Select, expand, dismiss, find paths
  26. 26. Neo4j Bloom 26 Perspective Business view of the graph Departmental views • Hiding PII • Styling Visualization GPU Accelerated Visualization High performance physics & rendering Exploration Direct graph interactions Select, expand, dismiss, find paths Inspection Node + Relationship details Browse from neighbor to neighbor
  27. 27. Neo4j Bloom 27 Perspective Business view of the graph Departmental views • Hiding PII • Styling Visualization GPU Accelerated Visualization High performance physics & rendering Exploration Direct graph interactions Select, expand, dismiss, find paths Inspection Node + Relationship details Browse from neighbor to neighbor Editing Create, Connect, Update Code-free graph changes
  28. 28. Neo4j Bloom 28 Perspective Business view of the graph Departmental views • Hiding PII • Styling Visualization GPU Accelerated Visualization High performance physics & rendering Exploration Direct graph interactions Select, expand, dismiss, find paths Inspection Node + Relationship details Browse from neighbor to neighbor Editing Create, Connect, Update Code-free graph changes Search Near-natural Language Search Full-text search • Graph patterns • Custom Search Phrases
  29. 29. 29 ● Search with type- ahead suggestions ● Category icons and color scheme ● Visualize, Explore and Discover ● Pan, Zoom and Select ● Property Browser and editor Neo4j Bloom User Interface
  30. 30. Graph Perspective 30 Manage visibility and reduce clutter, revealing the right information to the right users. • Selective Relationships • Selective Property Visibility • Categorized Raw Entities • Defined Entity Patterns* Need-to-know Details • Departmental Views • Hide Personally Identifiable Info • Structural-only Dev view Rich Entities* • Truck with Packages • Person with Aliases • Blog Post with Comments • Component with Parts
  31. 31. 31 Northwind Graph
  32. 32. 32 Northwind Shipping Dept.
  33. 33. 33 Northwind Sales Dept.
  34. 34. Graph Search 34 Ask Bloom what you’re looking for using idiomatic phrases based on the graph structure and content. • Search Everywhere • Find Graph Patterns • Customize Search Phrases “Tom Hanks” “Tom Hanks Movies” “From Tom Hanks to Kevin Bacon”
  35. 35. APPLICATION SERVERS 35 Neo4j Clustering - Causal Cluster Replica Servers Query, View Core Servers Synced Cluster CORE SERVERS READ REPLICAS Async Replication Writes (transactions) Reads (Graph Queries)
  36. 36. 36 Neo4j Graph Algorithm Library Finds the optimal path or evaluates route availability and quality Pathfinding & Search Determines the importance of distinct nodes in the network Centrality Evaluates how a group is clustered or partitioned Community Detection
  37. 37. 37 Neo4j Graph Algorithm Library - Parallel Breadth First Search & DFS - Shortest Path - Single-Source Shortest Path - All Pairs Shortest Path - Minimum Spanning Tree - A* Shortest Path - Yen’s K Shortest Path - K-Spanning Tree (MST) - Degree Centrality - Closeness Centrality - Betweenness Centrality - PageRank - Wasserman & Faust Closeness Centrality - Harmonic Closeness Centrality - Dangalchev Closeness Centrality - Approx. Betweenness Centrality - Personalise PageRank - Triangle Count - Clustering Coefficients - Strongly Connected Components - Label Propagation - Louvian Modularity - Louvian (Multi-step) - Balanced Triad (identification) - Connected Components (Union Find) - Euclidean Distance - Cosine Similarity - Jaccard Similarity - Random Walk - One Hot Encoding
  38. 38. Questions? 38
  39. 39. Thank You! ivan@neo4j.com 39

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