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© 2023 Neo4j, Inc. All rights reserved.
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Graphing Relational Databases
Ghlen Nagels (https://nagels.tech, @GhlenNagels)
Freelance Consultant @ Neo4j, aRes Travel Inc, NTC & more

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Plan
Introduction
When To Migrate
Example Project
In-Depth Cases
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Introduction
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Introduction: Experience
Telecommunications
Life sciences
- Provided Multiple Migration Services
- PHP Driver Author & Maintainer
- Authored much material on this
- Mapped ORM/Query Builder from
Relational to Graph
- Provided Multiple Tutorials / Workshops
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Introduction: Requirement Essentials
Telecommunications
Life sciences
- Understanding of basic SQL principles
- Understanding of basic Cypher/CQL query language
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Introduction: How to get the most out of this
Telecommunications
Life sciences
- Experience with migrating schemas, data and systems
- Have Docker installed
- Understand cursors and the impact on memory
- Have experience in PHP
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Introduction: Frustration
Telecommunications
Life sciences
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The promised Land
[LMW][AN]M[PJT]+ → [LMW][AN][MG][PJT]+
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https://www.youtube.com/watch?v=dFgkXxoSwWo

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Ecosystem

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Path To The Promised Land: Option 1
Telecommunications
Life sciences
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Path To The Promised Land: Option 2
Telecommunications
Life sciences
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Path to the promised land:
Telecommunications
Life sciences
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The ecosystem does not necessarily
help you get there
Proper planning and understanding
your data model does

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Introduction: Mindset
Telecommunications
Life sciences
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- Confidence:
Relational Database Models can be Directly translated to Graphs
- Understanding:
The real challenge is understanding you own Data Model
- Patterns:
Every DB pattern has a solution on how to translate it to Graphs
(we’ll see 4 patterns today)

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When to Migrate
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When to Migrate
Telecommunications
Life sciences
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- Holistic Problem
- Always complicated
- Risk versus Reward
A collection of indicators help decide

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Migration Indicator: Slow join operations
Telecommunications
Life sciences
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- Relationships are not a first class-citizen
in Relational Databases
- Recursive joins and big datasets put a chokehold
on Your Applications
- Almost all other Indicators are actually
Sub-optimal solutions to this

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Migration Indicator: Caches for everything
Telecommunications
Life sciences
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- A cache is a great tool to optimise performance
- Premature optimisation is the root of all evil
- Caching introduces data duplication
- Cache flushing is a horrible problem to have
especially in complex server topologies

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Migration Indicator: Esoteric Solutions (for simple problems)
Telecommunications
Life sciences
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- Ever come up with your own indexing system?
- Polymorphism (see later)
- Materialised views
- Database triggers
- Dynamic queries without parameters
- Verrrryyy lazy loading
- …

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Migration Indicator: Non Normalised Tables
Telecommunications
Life sciences
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- They actually taught me this in college
- Willfully introduces data duplicity to improve performance

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Migration Indicator: Lots of DB Migrations
Telecommunications
Life sciences
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- Constantly changing data models
- Are being hampered by a system with forced schemas
- Changing, moving and splitting tables are expensive
- Complicates CI

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Migration Indicator: Painful Data Science Stack
Telecommunications
Life sciences
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Example Project
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Example Project: The Schema
Telecommunications
Life sciences
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Example Project: Key Takeaways
Telecommunications
Life sciences
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- Simple Join: Comments have one user
- Self Join: Articles and Comments are hierarchical
- Pivot Table: An Article may contain multiple Tags
A Tag can tag multiple Articles
- Polymorphism: Categories are all-encompassing

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Example Project: Goals
Telecommunications
Life sciences
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- Query Simplications
- Speed upgrades
- Easy Migration

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Neo4j Workshop
⚡ Let’s get down to business 💻
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https://github.com/transistive/book-example

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Query Simplifications: Simple Join
Telecommunications
Life sciences
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Query Simplifications: Self Join
Telecommunications
Life sciences
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Query Simplifications: Pivot Table
Telecommunications
Life sciences
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Query Simplifications: Polymorphism
Telecommunications
Life sciences
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Query Simplifications: Polymorphism
Telecommunications
Life sciences
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Query Simplifications: Key Insight
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All four cases map to the same data solution

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Query Simplifications: Another Unfair Example
Telecommunications
Life sciences
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How to query the hierarchical structure of articles?

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Query Simplifications: Another Unfair Example
Telecommunications
Life sciences
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Query Simplifications: Another Unfair Example
Telecommunications
Life sciences
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In-Depth Cases
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Overall Strategy
Telecommunications
Life sciences
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- Identify what is a Node and a Relationship
- Insert the Nodes with the original identification
in the origin database
- Connect the Relationships using the original identification in
the original database. AKA the FINAL JOIN
- Optional: Wipe original database identification

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In-Depth Cases: Nodes
Telecommunications
Life sciences
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In-Depth Cases: Simple joins & self joins
Telecommunications
Life sciences
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- The connection information is in both pair of nodes
- MERGE is your friend
- Introduce a cartesian product with a where
expression limiting the matches
- Potentially optimise performance with Indexes
(Congratulations, you just reinvented foreign keys in a graph database)
- Use Limit + Result Summary to chunk the query if required

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In-Depth Cases: Relationships
Telecommunications
Life sciences
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In-Depth Cases: Pivot tables
Telecommunications
Life sciences
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- The pivot table is the relationship
- Use the identifying information to match a cartesian product,
limited through a Where Expression
- All other rules apply
- Remove the Pivot Table Nodes

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In-Depth Cases: Polymorphism
Telecommunications
Life sciences
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- Treat the polymorphic table as a pivot table
- Use application level logic to translate the table names to
node labels

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Neo4j Workshop
⚡ Let’s get down to business 💻
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back to the same code

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Let’s stay connected
with the community
dev.neo4j.com/chat

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Let’s stay connected
ghlen@nagels.tech
Whatsapp
+32 485 49 64 90

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© 2023 Neo4j, Inc. All rights reserved.
Thank You!
Special thanks to: Martin O’Hanlon and
Jennifer Reif
Questions?