The document compares relational and graph databases, noting that relational databases require more joins when querying normalized data which increases query time. Graph databases provide an alternative by storing data in nodes and edges, allowing for faster index-free adjacency queries. Neo4j is highlighted as an example of a graph database that is fully ACID compliant and uses the Cypher query language.

1. Graph
Databases

2. The problem
with
Relational
databases
• We normalize data to manage redundancy.
• Then there will be many tables. When
querying data we have to use more joins.
• When database have more data queries
take more time to execute.
• We use indexes to minimize this time.
(Indexed adjacency).

3. A Solution
• Nosql databases was invented.
• But there was a tradeoff.
• ACID was not supported for nosql.

4. Graph
Databases
• A graph database is any storage system
that uses graph structures with nodes and
edges, to represent and store data.
• Query using index free adjacency.
Therefore query is faster.

5. Relational Databases Vs Graph Databases

6. Relational Databases Vs Graph Databases

8. Neo4j
• A graph database.
• Fully ACID compliant.
• Uses Cypher query
language(CQL).

9. CRUD
• Create a node
• CREATE (:Person
{id:"P01",name:"John",age:"20"});
• Retrieve a node
• MATCH (p:Person {id:"P01"}) RETURN (p)
• Update node property
• MATCH (p:Person {id:"P01"}) SET
p.age="25";
• Delete a node
• MATCH (p:Person) WHERE id="P001"
DETACH DELETE (p);

10. Relationships
• Create relationship between existing
nodes.
• MATCH
(p:Person{id:"P01"}),(c:Car{id:"C01
"}) CREATE (p) -[:HAS]-> (c);

11. MERGE Vs CREATE
MERGE (c:Car{id:"C01"}) MERGE
(p:Person{id:"P02",name:"doe"}) -[:OWNS]-
> (c);

12. What is the correct query to
retrieve P01's car?
1. MATCH(c:Car) -[:OWNS]-> (p:Person{id:"P01"})
RETURN c;
2. MATCH (c:Car) <-[:OWNS]- (p:Person{id:"P01"})
RETURN c;
3. MATCH (c:Car) -[:OWNS]- (p:Person{id:"P01"})
RETURN c
4. MATCH (c:Car) -[]- (p:Person{id:"P01"}) RETURN c
5. MATCH(c:Car) -- (p:Person{id:"P01"}) RETURN c
6. MATCH (c:Car) <-- (p:Person{id:"P01"}) RETURN c

13. Constraints
Create
CREATE CONTRAINTS ON (p:PERSON) ASSERT
p.name IS UNIQUE;
Drop
DROP CONSTRAINT ON (p:Person) ASSERT
p.propertyName IS UNIQUE;

14. Aggregating functions
Owners count of the car(P01)
match (c:Car {id:"C01"}) <-
[:OWNS]- (p) return count(p) as
ownersCount;

15. Find the car that owns by P01 and P02
• MATCH (:Person{id:"P01"}) -[:OWNS]-> (c) <-
[:OWNS]- (:Person{id:"P02"}) RETURN c;
• MATCH (p1:Person{id:"P01"}),(p2:Person{id:"P02"})
MATCH (p1) -[:OWNS]-> (c) <-[:OWNS]- (p2) return
c

16. Find the car that owns by P01,P02 and P03
MATCH
(p3:Person{id:"P03"}),(p1:Person{id:"P01"}),(p2
:Person{id:"P02"})
MATCH (p1) -[:OWNS]-> (c:Car) <-[:OWNS]-
(p2)
MATCH (c) <-[:OWNS]- (p2) RETURN (c);

17. Regular Expressions =~
MATCH (p:Person) WHERE p.name =~"A.+"
RETURN p;