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structr
The Evolution and Future of
Graph Technology: Intelligent Systems
Data Natives 2018, Berlin
Axel Morgner, Founder and CEO Structr
structr
Most Popular Database Model
structr
Growth Factors
What happened here?
structr
Some Key Events
Neo4j 2.0Neo4j 2.0
Panama Papers Effect
GQL Manifesto
structr
A new Sta(nda)r(d) is Born!
structr
Why?
structr
There must be some good reasons…
New Abstractions?Graph Theory?
Images published on Wikipedia:
CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=112920
CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=990540
CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=851840
CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=20544977
checkEmail
:Computer :Server
sendUnsentEmail
newEmail
response
[newEmail] downloadEmail
deleteOldEmail
structr
checkEmail
:Computer :Server
sendUnsentEmail
newEmail
response
[newEmail] downloadEmail
deleteOldEmail
There must be some good reasons…
New Abstractions?Graph Theory?
1736 1997
1999
1976
Images published on Wikipedia:
CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=112920
CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=990540
CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=851840
CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=20544977
structr
Simplification
Property Graph Model
structr
Simplification & Technology
Property Graph Model (Native) Graph Database
structr
Property Graph Model
checkEmail
:Computer :Server
sendUnsentEmail
newEmail
response
[newEmail] downloadEmail
deleteOldEmail
structr
Graph Database
checkEmail
:Computer :Server
sendUnsentEmail
newEmail
response
[newEmail] downloadEmail
deleteOldEmail
structr
Evolution of (Graph) Use Cases
Data Volume
Complexity
Content Management
Fraud Detection
Social Networks
Risk Management
Machine Learning
Artificial Intelligence
Master Data Management
Network Operations
Configuration Management
Recommendation Engines
Knowledge Graphs
Internet of Things
Natural Language Processing
Decision Trees
Contextual Learning
structr
Intelligent Systems
Evolution of (Graph) Use Cases
Data Volume
Complexity
Content Management
Fraud Detection
Social Networks
Risk Management
Machine Learning
Artificial Intelligence
Master Data Management
Network Operations
Configuration Management
Recommendation Engines
Knowledge Graphs
Internet of Things
Natural Language Processing
Decision Trees
Contextual Learning
structr
Why are Graphs the Future?
●
Best abstraction for the real world:
– Concepts and relations
– Physical objects and their
interactions (particles, attraction
and repulsion forces, bio-chemical
reactions)
structr
●
Most generic model,
flexible and easy to understand
●
Most direct implementation =
least impedance mismatch
●
No joins/map-reduce
●
Least ‘moving’ parts
(shortest stack traces)
Why Graph Technology?
structr
Why Graphs for ML and AI?
●
Matrix/tensor algorithms are limited to linear relations
●
Context/semantics are best modeled as (knowlege) graph
●
Graphs are good for sparse data (no empty values)
●
Graph algorithms are more efficient than brute force
●
Neural networks are graphs
structr
API
Evolution of Graph Technology
structr
Query
Language
API API
Evolution of Graph Technology
structr
Query
Language
API API API
Query
Language
ETL
Evolution of Graph Technology
structr
Query
Language
API API API API
Admin
Analytics
Applications
Query
Language
Query
Language
Visualization
Drivers
ETL ETL
Evolution of Graph Technology
structr
Query
Language
API API API API
Admin
Analytics
Applications
Query
Language
Query
Language
Visualization
Drivers
ETL ETL
API
Admin
Analytics
Applications
Query
Language
Visualization
Drivers
ETL
Application and
Integration Platform
Evolution of Graph Technology
structr
structr
Thank You!
●
Questions & Demo:
Please come to our booth
●
Follow @structr on Twitter
●
https://structr.com

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