Graph databases
An overview
Natalia Oskina
Zuhlke Engineering Ltd
Graph Databases
An overview
Natalia Oskina
Zuhlke Engineering
Title Text
Agenda
- CAP?
- What kind of a creature is Graph DB?
- Graph DB vs relational DB
- Is it a silver bullet? Downsides
- Examples
- Cypher vs SQL
- Is it applicable? Real Use cases
- Demo
CAP theorem
- Consistency - all nodes see the same data at the same time
Brewer's theorem
- Availability - every request receives a response about whether it succeeded or failed
- Partition tolerance - the system continues to operate despite arbitrary partitioning due to network failures
What is a graph?
G = (V, E)
Graph database
"No broken links"
- Nodes
- Relationships
- Properties
Graph database
- If you would need to represent a system with all data of every movie ever made, how would you model it?
- You need to cover movie names, actors, directors, budget, dates, costs, location, ratings, shows, tickets...
What about Bacon number?
Graph DB vs Relational DB
Graph DB vs Relational DB
Graph DB vs Relational DB
- Chaotic data model. Irregualar, complex structure
- Highly complex relationships between entities
- Relationships are very different
- Check only relationships of the node, not the whole database
Examples
- Neo4J (Java, .Net, Python, JavaScript)
- AllegroGraph (C#, C, Java, Lisp, Python)
- Oracle Spatial and Graph ( Java, PI/SQL)
- AngoDB(C, C++, JavaScript)
Neo4J
- JVM Based
- Billions of entities
- Support ACID
- Using Cypher
Cypher
Functions like: WHERE, ORDER BY, SKIP LIMIT, AND, p.unitPrice > 10
Select and Return Records
SQL
SELECT p.*
FROM products as p;
Cypher
MATCH (p:Product)
RETURN p;
Field Access, Ordering and Paging
SQL
SELECT p.ProductName, p.UnitPrice
FROM products as p
ORDER BY p.UnitPrice DESC
LIMIT 10;
Cypher
MATCH (p:Product)
RETURN p.productName, p.unitPrice
ORDER BY p.unitPrice DESC
LIMIT 10
Downsides
- Use a lot of space
- Relational DB is much faster when operating a huge number of records
- Licence is expensive
Panama Papers
Panama Papers
Demo
