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![Cypher: Powerful and Expressive Query Language
KNOWS
Dan Ann
MATCH (:Person { name:“Dan”} ) -[:KNOWS]-> (:Person { name:“Ann”} )
LABEL PROPERTY
NODE NODE
LABEL PROPERTY](https://image.slidesharecdn.com/11-stefan-kolmar-slides-161207152056/85/Next-generation-Polyglot-Architectures-using-Neo4j-by-Stefan-Kolmar-24-320.jpg)
![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
Express Complex Queries Easily with Cypher
Find all direct reports and how
many people they manage,
up to 3 levels down
Cypher Query
SQL Query](https://image.slidesharecdn.com/11-stefan-kolmar-slides-161207152056/85/Next-generation-Polyglot-Architectures-using-Neo4j-by-Stefan-Kolmar-25-320.jpg)
![What is a NaBve Graph Database?
Applica<on
MATCH (:Person { name:“Dan”} )
-[:KNOWS]->
(:Person { name:“Ann”} )
Processing
Engine](https://image.slidesharecdn.com/11-stefan-kolmar-slides-161207152056/85/Next-generation-Polyglot-Architectures-using-Neo4j-by-Stefan-Kolmar-28-320.jpg)
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Next generation Polyglot Architectures using Neo4j by Stefan Kolmar
The document discusses the need for polyglot architectures in enterprises driven by data explosion, IoT, and cloud computing, emphasizing the requirement for handling large-scale connected data. It highlights the advantages of using Neo4j as a native graph database, including improved query performance, operational efficiency, and flexibility over traditional relational databases. Case studies demonstrate significant performance improvements and reduced complexity in various applications after transitioning to Neo4j.
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Next generation Polyglot Architectures using Neo4j by Stefan Kolmar
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- 3. Agenda • Drivers for change in enterprises • Requirements created for polyglot architecture • Tradi<onal approaches • Benefits of using graph technology • Neo4j as na<ve GraphDB • Architectures and Ecosystems • Case studies • Conclusions Admin
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- 9. Requirements created for polyglot architecture • Ability to handle large scale data volumes • High availability 24x7 • Open interfaces • Structure data to take advantage of connec<ons • Ability to query connected data on demand • Flexibility to connect and query data with different schema -> Using the technology which fits best doing the job Admin
- 10. TradiBonal approaches • Using RDBMS systems: • En<ty rela<onship models • Logical and physical Schema • SQL queries Admin
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- 14. What is the problem with that? • Understandable for business users? • Agility? • Needs effort to materialize rela<onships • Logical versus physical data model? • Op<miza<on needed to perform queries?
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- 16. What is themost powerful database in the world?
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- 22. CAR name: “Dan” born: May 29, 1960 twifer: “@dan” name: “Ann” born: Dec 5, 1995 since: Jan 10, 2011 brand: “Volvo” model: “V70” Property Graph Model Components Nodes • The objects in the graph • Can have name-value proper@es • Can be labeled RelaBonships • Relate nodes by type and direc<on • Can have name-value proper@es FATHER OF LIVES WITH LIVES WITH PERSON PERSON
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- 29. Agenda • Drivers for change in enterprises • Requirements created for polyglot architecture • Tradi<onal approaches • Benefits of using graph technology • Neo4j as na<ve GraphDB • Architectures and Ecosystems • Case studies • Conclusions Admin
- 30. PaTerns in Neo4j architectures • Primary Store • Reads + Write • Secondary Store • Mostly read, scheduled batch updates • ODS / MDS • Mostly read, scheduled batch updates + integra<on logic
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- 32. Original architecture 500 requests /sec Middleware services Backend Backend Backend Channel Channel Channel 42 channels 35 systems
- 33. New architecture 500 requests /sec Middleware services Backend Backend Backend Channel Channel Channel 42 channels 35 systems
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- 40. Who else uses Neo4j as a data source to feed mission criBcal applicaBons? • World’s largest parcel service • They no<ced that they would not have been able to deliver packages by Christmas 2013 • Hierarchical rou<ng system (RDBMS backed) • Replaced it with Neo4j using lateral rou<ng • Value: • Minimized <me • Maximized usage of road network • Recommenda<on engines • Fraud detec<on / preven<on architectures
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- 43. ODS / MDS case: Gov. Agency • The graph integrates data from mul<ple sources • ODS: Addi<onal opera<ons on the integrated data • MDS: Provide reference data to other opera<onal systems • European government agencies
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- 48. Conclusions: • Polyglot architectures are required to sa<sfy the needs exis<ng and coming • Neo4j na<ve graph database provides a compete<ve edge: • Agility • Flexibility • Opera<onal Efficiency • Time to Market • More informa<on: • www.neo4j.com • Stefan.Kolmar@neo4j.com
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