Best Practices for Getting to Production with DataStax Enterprise Graph

Five Tips for
Getting to
Production with
DataStax
Enterprise Graph
1 © DataStax, All Rights Reserved.

A robust, scale-out graph database that focuses on storing, processing,
and acting on highly connected and complex data relationships in real-
time.
DataStax Enterprise (DSE) Graph
© DataStax, All Rights Reserved. Confidential2

• Customer 360
• Personalization
• Recommendations
• Fraud Detection
• Internet of Things
• Asset Management
• Data Integration
Common DSE Graph Use Cases
3 © DataStax, All Rights Reserved. Confidential

Integrating data silos and
exploring neighborhoods to
provide personalized user
experience in real-time.
What is Customer 360 (C360)?
Location
Social
Orders
Account
Contact
Feedback
Devices
360°
Customer
Channels

1. Know Your Data
Distributions

Ask Yourself...
What relationships exist currently or
could possibly exist in the data?1
Location
Social
Orders
Account
Contact
Feedback
Devices
360°
Customer
Channels

Ask Yourself...
Which of the identified relationships
are important?
2
Location
Social
Orders
Account
Contact
Feedback
Devices
Customer
Channels

Ask Yourself...
What is the distribution of those
relationships?
are important?
2
3
Email to Customer Distribution
...
Number of Customers
CountofEmails

Ask Yourself...
What is the distribution of those
relationships?
are important?
2
3
Email to Customer Distribution
...
Number of Edges (Degree)
CountofEmails

2. Know Your Access
Patterns… As Much as
Possible

Data Modeling
“
The paradigm shift is that
we write our data according to
how we are going to read it.
Nate McCall on the journey of Apache Cassandra during DataStax Accelerate

Relational vs. Cassandra Data Modeling
Application
Models
Data
Data
Models
Application
Relational Cassandra

Relational vs. Cassandra vs Graph Data Modeling
Models
Data Application
Application
Models
Data
Data
Models
Application
Relational Cassandra
Graph

Common C360 Questions
• Who is this customer?
• What is their name, location,
gender, and age?
• What has this customer recently
purchased online or in stores?
• What feedback have they left about
those purchases?
• Who is this customer related to?
• How influential is this customer?
Location
Social
Orders
Account
Contact
Feedback
Devices
Customer
Channels

Common C360 Queries
gender, and age?
those purchases?
Location
Social
Orders
Account
Contact
Feedback
Devices
Customer
Channels

Conceptual Data Model
gender, and age?
those purchases?

Logical Data Model
• An entity with a single property and an average branching factor of one is a good
indication that the entity should be a property rather than a vertex.
• An entity that has a high median branching factor should be considered for properties
as opposed to vertices.

3. Optimize Query
Performance

Understand Branching Factor
Traversal time is
roughly
proportional to the
number of edges
and vertices
visited.

Filter Vertices out Along the Way
If you know which
vertices you are not
looking for, avoid
walking to them.

Pick the Best Starting Point
Consider where
your traversal
starts - do you walk
along less edges
when you start at
the black vertex or
the red vertex?

Go Back to the Data Model
Can you optimize
the path from black
to red by adding a
short-cut edge?

4. Design a Supernode
Strategy

What is a supernode?
A vertex with a disproportionately high
level of connected edges.
Causes problems such as:
• performance issues
• stability issues
• issues with visualization
• partial or incorrect results

What should you do if you find a supernode?
Try to model this
vertex as a
property.
Consider a
supernode
optimization
strategy.
Validate and clean
data on ingestion.
RIGHT-SKEWED
YES
NO YES
LEFT-SKEWED
NO
What does
the
distribution
look like?
Is your data
the sole
source of
truth?
Is the
data
valid?

Try to model this
vertex as a
property.
Consider a
supernode
optimization
strategy.
Validate and clean
data on ingestion.
YES
NO YES
LEFT-SKEWED
NO
What does
the
distribution
look like?
Is your data
the sole
source of
truth?
RIGHT-SKEWED
Is the
data
valid?

Try to model this
vertex as a
property.
Consider a
supernode
optimization
strategy.
Validate and clean
data on ingestion.
RIGHT-SKEWED
YES
NO YES
LEFT-SKEWED
NO
What does
the
distribution
look like?
Is your data
the sole
source of
truth?
Is the
data
valid?

Supernode Strategy: Add an Edge Index
Edge indices, also called Vertex Centric Indices are local to a vertex,
and give the ability to find and traverse only the edges we need
without scanning all edges.
To leverage the index, filter on the edge during the traversal.

Supernode Strategy: Get More Specific
Make your vertices more granular by including another field in the ID
of the vertex.
vs.

If you have a known supernode, but the vertex is too complex to be a
property, you can avoid performance issues by only traversing in to
the vertex to gather information.
Supernode Strategy: Traverse In, but not Out

5. Embrace a Multi-Model
Approach

Using the Right Tool for the Problem
DSE
Core
DSE Analytics
DSE Search DSE Graph
Query Complexity
Simple Complex
Offline
Fast
Human
Fast
QueryLatency(p99)

Query: Who is this customer?
DSE
Core
DSE Analytics
Query Complexity
Simple Complex
Offline
Fast
Human
Fast
QueryLatency(p99)
Who is this
customer?

Query: What has this customer recently purchased?
DSE
Core
DSE Analytics
Query Complexity
Simple Complex
Offline
Fast
Human
Fast
QueryLatency(p99)
What has
this
customer
recently
purchased?
Who is this
customer?

Query: Who is this customer related to?
DSE
Core
DSE Analytics
Query Complexity
Simple Complex
Offline
Fast
Human
Fast
QueryLatency(p99)
What has
this
customer
recently
purchased?
Who is this
customer related to?
Who is this
customer?

Query: How influential is this customer?
DSE
Core
DSE Analytics
Query Complexity
Simple Complex
Offline
Fast
Human
Fast
QueryLatency(p99)
What has
this
customer
recently
purchased?
Who is this
How influential is
this customer?
Who is this
customer?

Final Multi-Model Approach
DSE
Core
DSE Analytics
Query Complexity
Simple Complex
Offline
Fast
Human
Fast
QueryLatency(p99)
What has
this
customer
recently
purchased?
Who is this
How influential is
this customer?
Who is this
customer?

DataStax Graph For Labs

DataStax Graph for Labs
“Model Once”
Support
Because solving
complex graph
problems requires
more than just a
graph database.
Inherits DSE
Core Benefits
Fast, scalable and
highly available for
mission critical
applications on
prem and in the
cloud.
Built by the
Experts
Designed and
tested by the core
contributors to
Apache Cassandra
and Tinkerpop.

DOWNLOAD: Visit downloads.datastax.com/#labs to get the new
Graph Engine.

Best Practices for Getting to Production with DataStax Enterprise Graph

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