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Neo4j Graph Platform Overview
Kurt Freytag
Director of Product Management - Neo4j Cloud
What Makes Neo4j Different?
What Makes Neo4j Different?
3
TRADITIONAL
DATABASES
Store and retrieve data
Real time storage & retrieval
Up to
3
Max #
of
hops
What Makes Neo4j Different?
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
What Makes Neo4j Different?
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
What Makes Neo4j Different?
Index-Free Adjacency
6
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”
What Makes Neo4j Different :
“Minutes to Milliseconds” Real-Time Query Performance
ACID Consistency Non ‘Graph-ACID’ DBMSs
8
Maintains Integrity Over Time
Guaranteed Graph Consistency
Becomes Corrupt Over Time
Not ‘Good Enough’ for Graphs
What Is Different In Neo4j?
ACID Graph Writes : A Requirement for Graph Transactions
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
Neo4j Graph Advantage: Foundational Components
1
2
3
4
5
6
Index-Free Adjacency
In memory and on flash/disk
vs
ACID Foundation
Required for safe writes
Full-Stack Clustering
Causal consistency
Language, Drivers, Tooling
Developer Experience,
Graph Efficiency, Type Safety
Graph Engine
Cost-Based Optimizer, Graph
Statistics, Cypher Runtime
Hardware Optimizations
For next-gen infrastructure
Neo4j Enterprise Maturity & Robustness
11
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
DBMS Market Evolution: Connections as Imperative
12
Column Family Document
Data Storage & Retrieval
for all new use cases
1990
Relational Key-Value
Data Storage & Retrieval
for specific use cases
Codd’s
Paper
1979
Oracle
IPO
1986
Graph
Connected Data
for specific use cases
2010
Neo4j
v1.0
2019
openCypher
Launch
Connected Data
for all new use cases
2025
GQL
1.0
Neo4j: Enabling the Connected Enterprise
Consumers of Connected Data
13
AI & Graph Analytics
• Sentiment analysis
• Customer
segmentation
• Machine learning
• Cognitive computing
• Community detection
Transactional Graphs
• Fraud detection
• Real-time recommendations
• Network and IT operations
management
• Knowledge Graphs
• Master Data Management
Discovery & Visualization
• Fraud detection
• Network and IT
operations
• Product information
management
• Risk and portfolio analysis
Data
Scientists
Business
Users
Application
s
15
Development &
Administration
Analytics
Tooling
Graph
Analytics
Graph
Transactions
Data Integration
Discovery & VisualizationDrivers & APIs
AI
Neo4j Graph Platform
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
Neo4j Graph Platform in 2019
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 Graph Platform in 2019
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
Neo4j Graph Platform in 2019
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 Graph Platform in 2019
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 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 in 2019
Neo4j Graph Platform: Where We Are Today
21
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 community has voted to
include Cypher in Spark 3.0
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
23
Graph Visualization Options for Neo4j
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 focused Publishing / Consumption focused
Smaller deployments Larger deployments
Perspective
Visualization
Exploration
Inspection
Editing
Search
24
Business view of the graph
Departmental views • Hiding PII • Styling
GPU Accelerated Visualization
High performance
physics & rendering
Direct graph interactions
Select, expand, dismiss, find paths
Node + Relationship details
Browse from neighbor to neighbor
Create, Connect, Update
Code-free graph changes
Near-natural Language Search
Full-text search • Graph patterns
• Custom Search Phrases
Neo4j Bloom
Features
Neo4j Bloom User Interface
25
Search with type-
ahead suggestions
Category icons and
color scheme
Visualize, Explore and
Discover
Pan, Zoom and Select
Property Browser and
editor
Graph Perspective
26
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
27 Northwind Graph
28 Northwind Shipping Dept.
29 Northwind Sales Dept.
Graph Search
30
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”
APPLICATION
SERVERS
31
Neo4j Clustering - Causal Cluster
Replica Servers
Query, View
Core Servers
Synced Cluster
CORE
SERVERS
READ
REPLICAS
Async Replication
Writes
(transactions)
Reads
(Graph Queries)
32
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
33
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
Questions?
34
Thank You!
kurt@neo4j.com
35

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Neo4j Graph Platform Overview, Kurt Freytag, Neo4j

  • 1. Neo4j Graph Platform Overview Kurt Freytag Director of Product Management - Neo4j Cloud
  • 2. What Makes Neo4j Different?
  • 3. What Makes Neo4j Different? 3 TRADITIONAL DATABASES Store and retrieve data Real time storage & retrieval Up to 3 Max # of hops
  • 4. What Makes Neo4j Different? 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. What Makes Neo4j Different? 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. What Makes Neo4j Different? Index-Free Adjacency 6
  • 7. 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” What Makes Neo4j Different : “Minutes to Milliseconds” Real-Time Query Performance
  • 8. ACID Consistency Non ‘Graph-ACID’ DBMSs 8 Maintains Integrity Over Time Guaranteed Graph Consistency Becomes Corrupt Over Time Not ‘Good Enough’ for Graphs What Is Different In Neo4j? ACID Graph Writes : A Requirement for Graph Transactions
  • 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 Neo4j Graph Advantage: Foundational Components 1 2 3 4 5 6 Index-Free Adjacency In memory and on flash/disk vs ACID Foundation Required for safe writes Full-Stack Clustering Causal consistency Language, Drivers, Tooling Developer Experience, Graph Efficiency, Type Safety Graph Engine Cost-Based Optimizer, Graph Statistics, Cypher Runtime Hardware Optimizations For next-gen infrastructure
  • 11. Neo4j Enterprise Maturity & Robustness 11 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
  • 12. DBMS Market Evolution: Connections as Imperative 12 Column Family Document Data Storage & Retrieval for all new use cases 1990 Relational Key-Value Data Storage & Retrieval for specific use cases Codd’s Paper 1979 Oracle IPO 1986 Graph Connected Data for specific use cases 2010 Neo4j v1.0 2019 openCypher Launch Connected Data for all new use cases 2025 GQL 1.0
  • 13. Neo4j: Enabling the Connected Enterprise Consumers of Connected Data 13 AI & Graph Analytics • Sentiment analysis • Customer segmentation • Machine learning • Cognitive computing • Community detection Transactional Graphs • Fraud detection • Real-time recommendations • Network and IT operations management • Knowledge Graphs • Master Data Management Discovery & Visualization • Fraud detection • Network and IT operations • Product information management • Risk and portfolio analysis Data Scientists Business Users Application s
  • 15. 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 Neo4j Graph Platform in 2019
  • 16. 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 Graph Platform in 2019
  • 17. 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 Neo4j Graph Platform in 2019
  • 18. 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 Graph Platform in 2019
  • 19. 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 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 in 2019
  • 20. Neo4j Graph Platform: Where We Are Today 21 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 community has voted to include Cypher in Spark 3.0 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. 23 Graph Visualization Options for Neo4j 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 focused Publishing / Consumption focused Smaller deployments Larger deployments
  • 22. Perspective Visualization Exploration Inspection Editing Search 24 Business view of the graph Departmental views • Hiding PII • Styling GPU Accelerated Visualization High performance physics & rendering Direct graph interactions Select, expand, dismiss, find paths Node + Relationship details Browse from neighbor to neighbor Create, Connect, Update Code-free graph changes Near-natural Language Search Full-text search • Graph patterns • Custom Search Phrases Neo4j Bloom Features
  • 23. Neo4j Bloom User Interface 25 Search with type- ahead suggestions Category icons and color scheme Visualize, Explore and Discover Pan, Zoom and Select Property Browser and editor
  • 24. Graph Perspective 26 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
  • 28. Graph Search 30 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”
  • 29. APPLICATION SERVERS 31 Neo4j Clustering - Causal Cluster Replica Servers Query, View Core Servers Synced Cluster CORE SERVERS READ REPLICAS Async Replication Writes (transactions) Reads (Graph Queries)
  • 30. 32 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
  • 31. 33 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