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01/12/2020
ML/AI & Graphs Synergy
#1 Graph Platform Neo4j Customer Use Cases Unite Neo4j
Neo4j SuperiorityGraph DB Popularity
7/10
20/25
7/10
Top Retail Firms
Top Financial Firms
Top Software Vendors
Anyway You Like It
Creator of the Property
Graph and Cypher language
at the core of the GQL ISO
project
Thousands of Customers
World-Wide
HQ in Silicon Valley, offices
include London, Munich,
Paris & Malmo
Industry Leaders use Neo4j
On-Prem
DB-as-a-Service
In the Cloud
+
+
+
The world’s most popular
graph database, as a cloud
service
Neo4j Graph Data
Science Library
Neo4j
Database
Neo4j
Bloom
™
2020-2030
Neo4j Aura Professional
+
+
+
+
+
The Shift
To The
Cloud
+
+
+
+
+
The Shift
To The
Cloud
Neo4j Aura Enterprise (Coming Soon)
Developers
at the
Center of
all we do
Developers at the center
Rise
of(Graph)
Data
Science
- Get more insight out
of the data you
already have.
- Add relationships
into your existing
workflows.
- Make better, more
accurate predictions.
Why Do Graph Data Science?
Neo4j Graph Data
Science Library
Scalable Graph
Algorithms & Analytics
Workspace
Native Graph
Creation & Persistence
Neo4j
Database
Visual Graph
Exploration
& Prototyping
Neo4j
Bloom
Practical Integrated Intuitive
Rise
of(Graph)
Data
Science
Neo4j for Graph Data Science
2014 2015 2016 2017 2018 2019 20202013
The Rise of the Graph Database
2010 - 2020: From Model to Category
Full
Potential of
the Property
Graph Model
Oct
2020
1.
2.
3.
Rank
4.
5.
6.
7.
8.
9.
10.
Neo4j
Microsoft Azure Cosmos DB
ArangoDB
OrientDB
Virtuoso
Amazon Neptune
JanusGraph
GraphDB
FaunaDB
Dgraph
DBMS Database Model
Graph
Multi-model
Multi-model
Multi-model
Multi-model
Multi-model
Graph
Multi-model
Multi-model
Graph
Score
Oct
2020
Sep
2019
51.33
32.01
5.55
5.47
2.57
2.48
2.40
2.09
1.79
1.68
+0.71
+0.34
-0.25
-0.01
+0.01
+0.13
+0.06
+0.67
+0.07
+0.06
Full
Potential of
the Property
Graph Model
The Rise of the Graph Database
2010 - 2020: From Model to Category
Highest possible scores in:
● Performance
● Scalability
● Workloads
● Data management
● Data loading/ingestion
● Queries/search
● Use cases
● API/extensibility
● Transactions
● High availability and
disaster recovery
● Deployment options
Full
Potential of
the Property
Graph Model
The Rise of the Graph Database
2010 - 2020: From Model to Category
Full
Potential of
the Property
Graph Model
The Rise of the Graph Database
2010 - 2020: Sweet Spot Use Cases
•
•
•
•
•
•
•
Neo4j’s Secret Sauce!
Neo4j Graph Data
Science
Neo4j
Database
Neo4j Bloom
Graph Data Science is a science-driven
approach to gain knowledge from the
relationships and structures in data,
typically to power predictions.
Rise
of(Graph)
Data
Science
What is Graph Data Science?
Rise
of(Graph)
Data
Science
o Get more insight out of the
data you already have.
o Add relationships into your
existing workflows.
o Make better, more accurate
predictions.
Why Do Graph Data Science?
Neo4j Graph Data
Science Library
Scalable Graph
Algorithms & Analytics
Workspace
Native Graph
Creation & Persistence
Neo4j
Database
Visual Graph
Exploration
& Prototyping
Neo4j
Bloom
Practical Integrated Intuitive
Rise
of(Graph)
Data
Science
Neo4j for Graph Data Science
Pathfinding
& Search
Similarity
Community
Detection
Centrality &
Importance
Graph
Embeddings
Link
Prediction
50+ Graph Algorithms & ML techniques
Flexible Analytics Workspace
Rise
of(Graph)
Data
Science
The Graph Data Science Library
• Degree Centrality
• Closeness Centrality
• Harmonic Centrality
• Betweenness Centrality & Approx.
• PageRank
• Personalized PageRank
• ArticleRank
• Eigenvector Centrality
• Shortest Path
• Single-Source Shortest Path
• All Pairs Shortest Path
• A* Shortest Path
• Yen’s K Shortest Path
• Minimum Weight Spanning Tree
• K-Spanning Tree (MST)
• Random Walk
• Breadth & Depth First Search
• Triangle Count
• Local Clustering Coefficient
• Connected Components (Union Find)
• Strongly Connected Components
• Label Propagation
• Louvain Modularity
• K-1 Coloring
• Modularity Optimization
• Euclidean Distance
• Cosine Similarity
• Node Similarity (Jaccard)
• Overlap Similarity
• Pearson Similarity
• Approximate KNN
• Adamic Adar
• Common Neighbors
• Preferential Attachment
• Resource Allocations
• Same Community
• Total Neighbors
... Auxiliary Functions:
• Random
graph generation
• Graph export
• One hot encoding
• Distributions & metrics
• Node2Vec
• Random Projections
• GraphSAGE
Rise
of(Graph)
Data
Science
50+ Graph Algorithms in Neo4j
Write Your Own
Algorithms
Machine Learning
Algorithms
Use matrix math and neural networks
to learn the structure of your graph
Train, store, and fit predictive
models within Neo4j
Leverage your embeddings to build
nearest neighbors graphs
Use our Pregel API to build your own
algorithms using our infrastructure
Graph Embeddings & Complex
Data Types
Model
Catalog
GDS 1.0
First enterprise
library for graph
data science.
Neo4j 4.0
Compatibility
GDS 1.2
GDS 1.1
Graph Mutability
& Expressivity
GDS 1.3
New Algorithms &
RBAC
Graph Native
Learning
GDS 1.4
Rise
of(Graph)
Data
Science
Introducing GDS 1.4
Graph algorithms to uncover
trends and patterns
Patterns
Pointers
Queries to answer questions
with connected data
Predictions
Graph-native ML learns the
topology of your graph to
uncover new facts
Rise
of(Graph)
Data
Science
Putting it all Together
NODES talks:
- Graph native learning: introducing GraphSAGE & the model catalog
- Write your own algorithms with the Pregel API
- Getting graph questions answered through Neo4j Bloom
Developers:
- Developer Guides: neo4j.com/developer/graph-data-science/
- GDS Sandbox: sandbox.neo4j.com/?usecase=graph-data-science
- GitHub: github.com/neo4j/graph-data-science
Books:
- Graph Algorithms: Practical Examples in Apache Spark & Neo4j:
neo4j.com/graph-algorithms-book/
- GDS For Dummies: neo4j.com/graph-data-science-for-dummies
Rise
of(Graph)
Data
Science
Neo4j Graph Data Science - Resources
38
Community
Vs
Enterprise
What is the difference Between
Community vs Enterprise?
Neo4j Enterprise Edition Neo4j Community Edition
Neo4j
Enterprise
Architecture
What is the Neo4j Enterprise Architecture
Neo4j Graph
Data Science
Neo4j
Databas
e
Neo4j
Bloom
Neo4j
Runes
Everywhere
Where can I deploy Neo4j?
On-Prem DaaS – Fully ManagedIn the Cloud (BYOL)
42

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Introduction to Neo4j

  • 2.
  • 3. ML/AI & Graphs Synergy #1 Graph Platform Neo4j Customer Use Cases Unite Neo4j Neo4j SuperiorityGraph DB Popularity
  • 4.
  • 5. 7/10 20/25 7/10 Top Retail Firms Top Financial Firms Top Software Vendors Anyway You Like It Creator of the Property Graph and Cypher language at the core of the GQL ISO project Thousands of Customers World-Wide HQ in Silicon Valley, offices include London, Munich, Paris & Malmo Industry Leaders use Neo4j On-Prem DB-as-a-Service In the Cloud
  • 6.
  • 7.
  • 8. + + + The world’s most popular graph database, as a cloud service
  • 9. Neo4j Graph Data Science Library Neo4j Database Neo4j Bloom ™
  • 10.
  • 11.
  • 14. + + + + + The Shift To The Cloud Neo4j Aura Enterprise (Coming Soon)
  • 15. Developers at the Center of all we do Developers at the center
  • 16. Rise of(Graph) Data Science - Get more insight out of the data you already have. - Add relationships into your existing workflows. - Make better, more accurate predictions. Why Do Graph Data Science?
  • 17. Neo4j Graph Data Science Library Scalable Graph Algorithms & Analytics Workspace Native Graph Creation & Persistence Neo4j Database Visual Graph Exploration & Prototyping Neo4j Bloom Practical Integrated Intuitive Rise of(Graph) Data Science Neo4j for Graph Data Science
  • 18. 2014 2015 2016 2017 2018 2019 20202013 The Rise of the Graph Database 2010 - 2020: From Model to Category Full Potential of the Property Graph Model
  • 19. Oct 2020 1. 2. 3. Rank 4. 5. 6. 7. 8. 9. 10. Neo4j Microsoft Azure Cosmos DB ArangoDB OrientDB Virtuoso Amazon Neptune JanusGraph GraphDB FaunaDB Dgraph DBMS Database Model Graph Multi-model Multi-model Multi-model Multi-model Multi-model Graph Multi-model Multi-model Graph Score Oct 2020 Sep 2019 51.33 32.01 5.55 5.47 2.57 2.48 2.40 2.09 1.79 1.68 +0.71 +0.34 -0.25 -0.01 +0.01 +0.13 +0.06 +0.67 +0.07 +0.06 Full Potential of the Property Graph Model The Rise of the Graph Database 2010 - 2020: From Model to Category
  • 20. Highest possible scores in: ● Performance ● Scalability ● Workloads ● Data management ● Data loading/ingestion ● Queries/search ● Use cases ● API/extensibility ● Transactions ● High availability and disaster recovery ● Deployment options Full Potential of the Property Graph Model The Rise of the Graph Database 2010 - 2020: From Model to Category
  • 21. Full Potential of the Property Graph Model The Rise of the Graph Database 2010 - 2020: Sweet Spot Use Cases
  • 22.
  • 25.
  • 27.
  • 28.
  • 29. Graph Data Science is a science-driven approach to gain knowledge from the relationships and structures in data, typically to power predictions. Rise of(Graph) Data Science What is Graph Data Science?
  • 30. Rise of(Graph) Data Science o Get more insight out of the data you already have. o Add relationships into your existing workflows. o Make better, more accurate predictions. Why Do Graph Data Science?
  • 31. Neo4j Graph Data Science Library Scalable Graph Algorithms & Analytics Workspace Native Graph Creation & Persistence Neo4j Database Visual Graph Exploration & Prototyping Neo4j Bloom Practical Integrated Intuitive Rise of(Graph) Data Science Neo4j for Graph Data Science
  • 32. Pathfinding & Search Similarity Community Detection Centrality & Importance Graph Embeddings Link Prediction 50+ Graph Algorithms & ML techniques Flexible Analytics Workspace Rise of(Graph) Data Science The Graph Data Science Library
  • 33. • Degree Centrality • Closeness Centrality • Harmonic Centrality • Betweenness Centrality & Approx. • PageRank • Personalized PageRank • ArticleRank • Eigenvector Centrality • Shortest Path • Single-Source Shortest Path • All Pairs Shortest Path • A* Shortest Path • Yen’s K Shortest Path • Minimum Weight Spanning Tree • K-Spanning Tree (MST) • Random Walk • Breadth & Depth First Search • Triangle Count • Local Clustering Coefficient • Connected Components (Union Find) • Strongly Connected Components • Label Propagation • Louvain Modularity • K-1 Coloring • Modularity Optimization • Euclidean Distance • Cosine Similarity • Node Similarity (Jaccard) • Overlap Similarity • Pearson Similarity • Approximate KNN • Adamic Adar • Common Neighbors • Preferential Attachment • Resource Allocations • Same Community • Total Neighbors ... Auxiliary Functions: • Random graph generation • Graph export • One hot encoding • Distributions & metrics • Node2Vec • Random Projections • GraphSAGE Rise of(Graph) Data Science 50+ Graph Algorithms in Neo4j
  • 34. Write Your Own Algorithms Machine Learning Algorithms Use matrix math and neural networks to learn the structure of your graph Train, store, and fit predictive models within Neo4j Leverage your embeddings to build nearest neighbors graphs Use our Pregel API to build your own algorithms using our infrastructure Graph Embeddings & Complex Data Types Model Catalog GDS 1.0 First enterprise library for graph data science. Neo4j 4.0 Compatibility GDS 1.2 GDS 1.1 Graph Mutability & Expressivity GDS 1.3 New Algorithms & RBAC Graph Native Learning GDS 1.4 Rise of(Graph) Data Science Introducing GDS 1.4
  • 35. Graph algorithms to uncover trends and patterns Patterns Pointers Queries to answer questions with connected data Predictions Graph-native ML learns the topology of your graph to uncover new facts Rise of(Graph) Data Science Putting it all Together
  • 36. NODES talks: - Graph native learning: introducing GraphSAGE & the model catalog - Write your own algorithms with the Pregel API - Getting graph questions answered through Neo4j Bloom Developers: - Developer Guides: neo4j.com/developer/graph-data-science/ - GDS Sandbox: sandbox.neo4j.com/?usecase=graph-data-science - GitHub: github.com/neo4j/graph-data-science Books: - Graph Algorithms: Practical Examples in Apache Spark & Neo4j: neo4j.com/graph-algorithms-book/ - GDS For Dummies: neo4j.com/graph-data-science-for-dummies Rise of(Graph) Data Science Neo4j Graph Data Science - Resources
  • 37.
  • 38. 38
  • 39. Community Vs Enterprise What is the difference Between Community vs Enterprise? Neo4j Enterprise Edition Neo4j Community Edition
  • 40. Neo4j Enterprise Architecture What is the Neo4j Enterprise Architecture Neo4j Graph Data Science Neo4j Databas e Neo4j Bloom
  • 41. Neo4j Runes Everywhere Where can I deploy Neo4j? On-Prem DaaS – Fully ManagedIn the Cloud (BYOL)
  • 42. 42