Cliff Notes: What Java Developers Need to Know About Graph Databases

Keeping up with database trends? Or learning for a project requirement? Or something else? In this session, we will hit the high points on graph databases and get Java developers what they need to get started quickly and successfully. From data model to applications, these are the Cliff Notes!

Transcript

1. Cliff Notes: What Java Developers Need to Know About Graph Databases Jennifer Reif Email: jennifer.reif@neo4j.com Twitter: @JMHReif Website: jmhreif.com
2. Who Am I? - Jennifer • Developer + Advocate • Continuous learner • Conference speaker • Blogger • Geek Jennifer Reif Email: jennifer.reif@neo4j.com Twitter: @JMHReif Website: jmhreif.com
3. It’s all about data • Applications are built on data • Ever had project where only features explained, not data? • How did it go? • Was product off of expectations?
4. Alternative: Domain-Driven Design (DDD) • Mutual understanding of domain, concepts • Iterations • Understanding data = better understanding of result • Better product, minimum functionality • Sanity check code
5. Simple or grand foundation?
6. Data storage
7. Databases • Database: a structured set of data held in a computer, especially one that is accessible in various ways • Relational? NoSQL? Other?
8. Relational Database (RDBMS) • Oracle: 1979
9. Relational Database • No data model limitations • Memory-efficient for both read and write • CPU-intensive • Difficult query language
10. Document Database • MongoDB: 2007 "customer" : { "id": "123", "firstName" : "Jane", "lastName" : "Doe", "DOB" : "03/12/1989", "department" : "Engineering", "phoneNumbers" : { { "type" : "office", "number" : "650-123-4567" } { "type" : "cell", "number" : "650-321-7654" } } "title" : "Director of QA" }
11. Document Database • Easy to query (No SQL) • Easy horizontal scalability • Little flexibility (relationships pre-baked in document) "customer" : { "id": "123", "firstName" : "Jane", "lastName" : "Doe", "DOB" : "03/12/1989", "department" : "Engineering", "phoneNumbers" : { { "type" : "office", "number" : "650-123-4567" } { "type" : "cell", "number" : "650-321-7654" } } "title" : "Director of QA" }
12. Graph Database • Neo4j: 2007
13. Graph Database • No CPU vs Memory/Storage tradeoff (as in relational dbs) • No benefit in non-relational data sets • Still a query language
14. Have to pick just one? • Polyglot persistence: using multiple persistence strategies, each serving a different need • “Using the right tool for the job”
15. Java Application Data Store Options • Relational • Straight JDBC • JDBC Template • JOOQ • JPA or Hibernate • NoSQL - Document • MongoDB • Graph • Neo4j
16. What is a graph?
17. What is a graph? • Much older than tech of the last decade… • Arose from solution need (then and now) Seven Bridges of Konigsberg problem. Leonhard Euler, 1735
18. Java domain • Find field changes between Java 17 and Java 8? • Update doc URL for a Class • Find most similar diffs (which affected same components)
19. Enter stage right - graphs • Document path (not just data) • Answering how and why • Understanding connections • Find alternates, impacts, etc • Produce better assumptions, decisions
20. Neo4j
21. Extremes in Development
22. Stability • ACID compliance • Relationships at write vs read • Scaling (vertical+horizontal)
23. Innovation • Cypher vs SQL • Schema-less vs schema-enforced • Graph modeling vs ERD • Integrations • Cloud/on-premises solutions
24. Java dev: Why Graph?
25. Java domain • Java Versions (i.e. 8, 11, 17) • Changes between versions over time • Diffs
26. Java Entity - Domain Class • Class • Entity/Object • Represents domain type • General outline for objects of that type • Variables/properties • Details for that entity • Values may not always exist • Constructor - instance of object • Each instance is unique object with varying info
27. Demo: Let’s create one
28. Java Domain Relationships • Adding relationships • Add variable as pointer to another object • Links entities together • Might have some annotations for mapping
29. Demo: Let’s add that
30. Graph Data Model
31. Property Graph • Node (vertex) • Relationship (edge)
32. Nodes • Represent objects or entities • Can be labeled JavaVersion VersionDiff
33. Nodes • Represent objects or entities • Can be labeled • May have properties JavaVersion VersionDiff version: “17” gaDate: 2021-09-14 fromVersion: “17.0.3+7-tem” toVersion: “1.6.0_45-oracle” JavaVersion version: “6” gaDate: 2006-12-12 codeName: “Mustang”
34. Relationships • Must have a type • Must have a direction FROM_NEWER JavaVersion VersionDiff version: “17”
35. Relationships • Must have a type • Must have a direction • May have properties M IG RATES versionSteps: 3 FROM_NEWER JavaVersion VersionDiff version: “17”
36. Relationships • Must have a type • Must have a direction • May have properties • Nodes can share multiple relationships M IG RATES versionSteps: 3 FROM_NEWER JavaVersion VersionDiff version: “17”
37. Label • A group of nodes • Like a category • Domain class :) Person
38. Label • A group of nodes • Like a category • Domain class :) Person Employee Customer
39. Property • Key-value pair • Associated with node or relationship • Like a variable name and value M IG RATES versionSteps: 3 JavaVersion version: “17” JavaVersion version: “6” gaDate: 2021-09-14 gaDate: 2006-12-12 codeName: “Mustang”
40. Demo model
41. Whiteboard-friendliness
42. JDK Full Data Model
43. JDK Data Model
44. Java devs: Why Choose Graphs? • Data model match - application to database • Less data model mapping = more efficient application coding
45. Other types of graphs? • Resource Description Framework (RDF) • Triples: subject (node), predicate (rel), object (node) • Often web-based data • Often XML format
46. Query in a Graph vs Relational DB
47. SQL vs Cypher SELECT j.JavaVersion, j.Status, j.GaDate, j.EolDate, d.fromVendor, d.fromVersion, d.toVendor, d.toVersion FROM JavaVersion j LEFT JOIN DiffList dl ON dl.JavaVersion = j.JavaVersion LEFT JOIN VersionDiff d ON dl.FromVersion = d.FromVersion; MATCH (j:JavaVersion)-[r:FROM_NEWER]->(d:VersionDiff) RETURN j, r, d; SQL Cypher JavaVersion VersionDiff DiffList JavaVersion VersionDiff
48. Cypher • Functional and visual • Based on ASCII-art • Declarative query language • Focuses on what to retrieve • Not how A B LIKES MATCH ( A ) - [ : LIKES] - > ( B )
49. Cypher: powerful and expressive Jennifer Neo4j WORKS_FOR CREATE (:Person { name: ‘Jennifer’}) -[:WORKS_FOR]-> (:Company { name: ‘Neo4j’}) NODE PROPERTY NODE PROPERTY LABEL LABEL
50. Cypher: read Jennifer Neo4j WORKS_FOR MATCH (:Person { name: ‘Jennifer’} ) -[:WORKS_FOR]-> ( whom ) 
 RETURN whom
51. Let’s Query!
52. Java Ecosystem • Language drivers • Framework support • Spring, Quarkus, Micronaut, etc • Connectors • APOC, Neosemantics, ETL, Spark, etc • Visualization tools • Import/export • Database integrations
53. Let’s code!
54. Keep in mind… • Relational • JPA or Hibernate ▪ Mismatch between models ▪ Set theory and relational algebra • Graph • Neo4j ▪ More object-oriented model ▪ Based on graph theory and network theory
55. Resources • Code: github.com/JMHReif/pouring-coffee-into-matrix-lombok • Neo4j AuraDB: bit.ly/neo4j-aura • Blog: bit.ly/jmhreif-blog Jennifer Reif Email: jennifer.reif@neo4j.com Twitter: @JMHReif Website: jmhreif.com