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THEYEAR OFTHE GRAPH:
DOYOU REALLY NEED A GRAPH DATABASE?
HOW DOYOU CHOOSE ONE?
The year of the graph: do you really need a graph database?The year of the graph: do you really need a graph database?
ABOUT ME
 Working with data since 1992
 Graph DBs since 2005
 Databases
 Modeling
 Research
 Analysis
 Consulting
 Entrepreneurship
 Journalism
THE PROBLEMWITH RELATIONAL DBS
 Not good at relations!
 * Unintuitive model
 * Hard to query
 * Does not scale
GRAPH USE CASES: OPERATIONAL APPS
 Image: Neo4j
GRAPH USE CASES: OPERATIONAL APPS
 Smart Home - IoT
 * LeadingTelco in the Nordics
 * 1,5 Million Homes
 * Real-time processing
GRAPH USE CASES: ANALYTICS
 Image: Stanley Wang
GRAPH USE CASES: ANALYTICS
 Drug Discovery
 * Leading Pharma
 * Data on genes, proteins, etc
 * Identification of causal relationships
GRAPH USE CASES: DATA INTEGRATION
 Image: Ontotext
GRAPH USE CASES: DATA INTEGRATION
 Knowledge Graph for Search
 * Leading Retailer in DACH
 * 200Million+ MAU, 300K+ search requests
 * Improve coverage, response time, bottomline
GRAPH USE CASES: MACHINE LEARNING
 Image: Oracle
GRAPH USE CASES: MACHINE LEARNING
 Anti-Fraud in real-time
 * LeadingTelco in China
 * 600 Million Users
 * Compliance, trust
KNOWLEDGE GRAPHS EVERYWHERE,
GRAPH DATABASES ASTHE FOUNDATION
GRAPH DATABASES ARE BOOMING..
SO HOW DOYOU CHOOSE ONE?
 Existing research is:
 * Outdated
 * Shallow
 * Expensive
 * Marketing oriented
EVALUATING GRAPH DATABASES:
HTTP://YEAROFTHEGRAPH.XYZ
 Premises:
 * Always up to date
 * Holistic evaluation
 *Value for money
 * Hands-on
 Why me:
 * Hands-on since 2005
 *Top-tier analyst since 2013
 * Independent
 Free Newsletter!
WHAT GRAPH DATABASES ARE NOT:
ANALYTICAL &VIZ FRAMEWORKS,THIN GRAPH LAYERS
REAL GRAPH DATABASES GO ALLTHEWAY
 Operational vs. Analytical
 * Fully-fledged graph API
 * Operations & Analytics
 * Future-proof, integrated
 Native vs. Non-native
 *Designed as a graph database
 * Storing data in a native format
 * Optimized for graph
GRAPH DATABASETYPES: LPG
(LABELED PROPERTY GRAPH)
 * Non-standard format, query
 * Poor schema support
 * Interoperability
 * Flexible, generic
 * Fast traversals
 * Scalability
LPG GRAPH DATABASE USE CASES
 Operational
 applications
 Graph
 Traversals
 Graph
 Algorithms
GRAPH DATABASETYPES: RDF
(RESOURCE DESCRIPTION FRAMEWORK)
 * W3C: Interoperability, Maturity
 * Rich & Flexible Schema
 * Semantics, Rules, Reasoning
 * Performance
 * Scalability
 * Complexity
RDF GRAPH DATABASE USE CASES
 Data Integration  Knowledge Graph  AI
GRAPH DATABASETYPES: MULTI-MODEL
(DOCUMENT, KEY-VALUE)
 * Flexibility
 *Tooling
 * May not be optimized for graph
 * May have to move data around
 * Lock-in (cloud vendors)
EVALUATION CRITERIA: HOLISTIC, DATA-DRIVEN
 Application Development
 * Engine & API
 * Data Model
 * Query Language
 DevOps
 * Interoperability
 * Deployment & Configuration
 Advanced Analytics
 *Advanced Graph
 *Visualization
 Vendor Credentials & Support
 *Vendor Credentials
 * Support & Community
EVALUATION CRITERIA:
PERFORMANCE & COST
 * Not all vendors participate in benchmarks
 * Most benchmarks are not done by 3rd party
 * Complex, demanding exercise
 * Hard to compare LPG vs RDF
 * Not all vendors have public pricing & license info
 * Considered, not included as data points
 * Informed judgement needs experience, hands-on
TAKEAWAY POINTS
 * Graph DBs are here to stay
 * Different Graph DB models
 LPG
 RDF
 Multi-model
 * Each best suited to different use cases
 * Evaluation is hard!
EVALUATING GRAPH DATABASES IS HARD..
BUT SOMEBODY HASTO DO IT
Impressive work. I’m not aware of another
source that is as comprehensive as this one.
JONATHAN LACEFIELD, SENIOR DIRECTOR
OF PRODUCT MANAGEMENT, DATASTAX
ENTERPRISE SERVER
We did not have the time,
resources, or expertise to
evaluate all options properly. If
we did, our choices would have
been different.
APPLICATIONARCHITECT
EVALUATING GRAPH DATABASES:
JUST DOTHE MATH
 * 30+ options
 * Costs time and money
 * Requires expertise
 * Lack of proper evaluation ->
 Sub-optimal decisions ->
 Report cost:
 1 Day ofTop-tier consultant
 Access to updates, consulting

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The year of the graph: do you really need a graph database? How do you choose one?

  • 1. THEYEAR OFTHE GRAPH: DOYOU REALLY NEED A GRAPH DATABASE? HOW DOYOU CHOOSE ONE? The year of the graph: do you really need a graph database?The year of the graph: do you really need a graph database?
  • 2. ABOUT ME  Working with data since 1992  Graph DBs since 2005  Databases  Modeling  Research  Analysis  Consulting  Entrepreneurship  Journalism
  • 3. THE PROBLEMWITH RELATIONAL DBS  Not good at relations!  * Unintuitive model  * Hard to query  * Does not scale
  • 4. GRAPH USE CASES: OPERATIONAL APPS  Image: Neo4j
  • 5. GRAPH USE CASES: OPERATIONAL APPS  Smart Home - IoT  * LeadingTelco in the Nordics  * 1,5 Million Homes  * Real-time processing
  • 6. GRAPH USE CASES: ANALYTICS  Image: Stanley Wang
  • 7. GRAPH USE CASES: ANALYTICS  Drug Discovery  * Leading Pharma  * Data on genes, proteins, etc  * Identification of causal relationships
  • 8. GRAPH USE CASES: DATA INTEGRATION  Image: Ontotext
  • 9. GRAPH USE CASES: DATA INTEGRATION  Knowledge Graph for Search  * Leading Retailer in DACH  * 200Million+ MAU, 300K+ search requests  * Improve coverage, response time, bottomline
  • 10. GRAPH USE CASES: MACHINE LEARNING  Image: Oracle
  • 11. GRAPH USE CASES: MACHINE LEARNING  Anti-Fraud in real-time  * LeadingTelco in China  * 600 Million Users  * Compliance, trust
  • 12. KNOWLEDGE GRAPHS EVERYWHERE, GRAPH DATABASES ASTHE FOUNDATION
  • 13. GRAPH DATABASES ARE BOOMING.. SO HOW DOYOU CHOOSE ONE?  Existing research is:  * Outdated  * Shallow  * Expensive  * Marketing oriented
  • 14. EVALUATING GRAPH DATABASES: HTTP://YEAROFTHEGRAPH.XYZ  Premises:  * Always up to date  * Holistic evaluation  *Value for money  * Hands-on  Why me:  * Hands-on since 2005  *Top-tier analyst since 2013  * Independent  Free Newsletter!
  • 15. WHAT GRAPH DATABASES ARE NOT: ANALYTICAL &VIZ FRAMEWORKS,THIN GRAPH LAYERS
  • 16. REAL GRAPH DATABASES GO ALLTHEWAY  Operational vs. Analytical  * Fully-fledged graph API  * Operations & Analytics  * Future-proof, integrated  Native vs. Non-native  *Designed as a graph database  * Storing data in a native format  * Optimized for graph
  • 17. GRAPH DATABASETYPES: LPG (LABELED PROPERTY GRAPH)  * Non-standard format, query  * Poor schema support  * Interoperability  * Flexible, generic  * Fast traversals  * Scalability
  • 18. LPG GRAPH DATABASE USE CASES  Operational  applications  Graph  Traversals  Graph  Algorithms
  • 19. GRAPH DATABASETYPES: RDF (RESOURCE DESCRIPTION FRAMEWORK)  * W3C: Interoperability, Maturity  * Rich & Flexible Schema  * Semantics, Rules, Reasoning  * Performance  * Scalability  * Complexity
  • 20. RDF GRAPH DATABASE USE CASES  Data Integration  Knowledge Graph  AI
  • 21. GRAPH DATABASETYPES: MULTI-MODEL (DOCUMENT, KEY-VALUE)  * Flexibility  *Tooling  * May not be optimized for graph  * May have to move data around  * Lock-in (cloud vendors)
  • 22. EVALUATION CRITERIA: HOLISTIC, DATA-DRIVEN  Application Development  * Engine & API  * Data Model  * Query Language  DevOps  * Interoperability  * Deployment & Configuration  Advanced Analytics  *Advanced Graph  *Visualization  Vendor Credentials & Support  *Vendor Credentials  * Support & Community
  • 23. EVALUATION CRITERIA: PERFORMANCE & COST  * Not all vendors participate in benchmarks  * Most benchmarks are not done by 3rd party  * Complex, demanding exercise  * Hard to compare LPG vs RDF  * Not all vendors have public pricing & license info  * Considered, not included as data points  * Informed judgement needs experience, hands-on
  • 24. TAKEAWAY POINTS  * Graph DBs are here to stay  * Different Graph DB models  LPG  RDF  Multi-model  * Each best suited to different use cases  * Evaluation is hard!
  • 25. EVALUATING GRAPH DATABASES IS HARD.. BUT SOMEBODY HASTO DO IT Impressive work. I’m not aware of another source that is as comprehensive as this one. JONATHAN LACEFIELD, SENIOR DIRECTOR OF PRODUCT MANAGEMENT, DATASTAX ENTERPRISE SERVER We did not have the time, resources, or expertise to evaluate all options properly. If we did, our choices would have been different. APPLICATIONARCHITECT
  • 26. EVALUATING GRAPH DATABASES: JUST DOTHE MATH  * 30+ options  * Costs time and money  * Requires expertise  * Lack of proper evaluation ->  Sub-optimal decisions ->  Report cost:  1 Day ofTop-tier consultant  Access to updates, consulting