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Neo4j Platform Overview
Ivan Zoratti
Director of Product Management - Neo4j Database
What Is Different In Neo4j?
What Is Different In Neo4j?
3
TRADITIONAL
DATABASES
Store and retrieve data
Real time storage & retrieval
Up to
3
Max #
of
hops
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
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
What Is Different In Neo4j?
Index-Free Adjacency
6
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”
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
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
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
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
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
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
Development &
Administration
Analytics
Tooling
Graph
Analytics
Graph
Transactions
Data Integration
Discovery & VisualizationDrivers & APIs
AI
Neo4j Graph Platform: Where We Are Today
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
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
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
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
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
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
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
Neo4j Bloom
22
Neo4j Bloom
23
Perspective
Business view of the graph
Departmental views • Hiding PII • Styling
Neo4j Bloom
24
Perspective
Business view of the graph
Departmental views • Hiding PII • Styling
Visualization
GPU Accelerated Visualization
High performance
physics & rendering
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
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
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
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
● 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
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 Northwind Graph
32 Northwind Shipping Dept.
33 Northwind Sales Dept.
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”
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
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
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?
38
Thank You!
ivan@neo4j.com
39

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GraphTour - Neo4j Platform Overview

  • 1. Neo4j Platform Overview Ivan Zoratti Director of Product Management - Neo4j Database
  • 2. What Is Different In Neo4j?
  • 3. What Is Different In Neo4j? 3 TRADITIONAL DATABASES Store and retrieve data Real time storage & retrieval Up to 3 Max # of hops
  • 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. 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. What Is Different In Neo4j? Index-Free Adjacency 6
  • 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. 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. 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. 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. 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. 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. 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 Development & Administration Analytics Tooling Graph Analytics Graph Transactions Data Integration Discovery & VisualizationDrivers & APIs AI Neo4j Graph Platform: Where We Are Today
  • 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 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 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 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 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. 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. 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
  • 23. Neo4j Bloom 23 Perspective Business view of the graph Departmental views • Hiding PII • Styling
  • 24. Neo4j Bloom 24 Perspective Business view of the graph Departmental views • Hiding PII • Styling Visualization GPU Accelerated Visualization High performance physics & rendering
  • 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. 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. 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. 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 ● 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. 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
  • 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. 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 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 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