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Relational DB
vs
Document (no-SQL) DB
vs
Graph DB
Explanation through Examples
Relational DB
 This example has one to one
mapping.
 Foreign key reference.
 Normalized Structure, no
redundancy.
 Unique identifier necessary for
primary key as well as foreign key.
Article ID Article Name Article Content Article Date Author ID
ar1 Some Article Some Content 20-Feb-2010 au1
ar2 Other Article Other Content 10-Nov-2019 au2
ar3 Another Article Another Content 15-Sep-2011 au2
Author ID Author Name Author DOB
au1 Classy Betty 03-Jan-1970
au2 Casual Sam 04-Mar-1960
Document DB (no-SQL)
 The same example from previous
slide is designed with one level
nesting in this structure.
 Author structures nested in Article
structures.
 Redundancy in author information,
but that is normal in view of faster
access.
 Unlike relational DB, unique
identifier not needed.
 Usually represented as JSON
structure (illustrated to the right) or
key-value store (illustrated in a later
slide).
[
{
"Article Name": "Some Article",
"Article Content": "Some Content",
"Article Date": "20-Feb-2010",
"Author": {
"Author Name": "Classy Betty",
"Author DOB": "03-Jan-1970"
}
},
{
"Article Name": "Other Article",
"Article Content": "Other Content",
"Article Date": "10-Nov-2019",
"Author": {
"Author Name": "Casual Sam",
"Author DOB": "04-Mar-1960"
}
},
{
"Article Name": "Another Article",
"Article Content": "Another Content",
"Article Date": "15-Sep-2011",
"Author": {
"Author Name": "Casual Sam",
"Author DOB": "04-Mar-1960"
}
}
]
Graph DB
 This example has one to one
mapping, explained as relations.
 Normalized Structure, no
redundancy.
 Graph consists of nodes and
relationship.
 Both nodes and relationship can
have additional properties.
Type Command
Articles
(Node)
CREATE
(ar1:Article {name:'Some Article',content:"Some Content",date:"20-Feb-2010"})
CREATE
(ar2:Article {name:'Other Article',content:"Other Content",date:"10-Nov-2019"})
CREATE
(ar3:Article {name:'Another Article',content:"Another Content",date:"15-Sep-2011"})
Authors
(Node)
CREATE (au1:Author {name:'Classy Betty',dob:'03-Jan-1970'})
CREATE (au2:Author {name:'Casual Sam',dob:'04-Mar-1960'})
Authored By
(Relationship)
CREATE (ar1)-[:AUTHORED_BY]->(au1)
CREATE (ar2)-[:AUTHORED_BY]->(au2)
CREATE (ar3)-[:AUTHORED_BY]->(au2)
Relational DB
 This example has many to many
relationship.
 Foreign key reference in a separate
mapping table.
 Normalized Structure, no
redundancy.
 Unique identifier necessary for
primary key as well as foreign key.
Article ID Article Name Article Content Article Date
ar1 Some Article Some Content 20-Feb-2010
ar2 Other Article Other Content 10-Nov-2019
ar3 Another Article Another Content 15-Sep-2011
Author ID Author Name Author DOB
au1 Classy Betty 03-Jan-1970
au2 Casual Sam 04-Mar-1960
Author ID Article ID
au1 ar1
au2 ar1
au2 ar2
au1 ar3
au2 ar3
Document DB (no-SQL)
 The same example from previous
slide is designed with one level
nesting in this structure.
 The structure shows Author
structures nested in Article
structures.
 Redundancy in author information,
but that is normal in view of faster
access.
 The nested modelling is predefined
in view of the consumer application.
 Unlike relational DB, unique
identifier not needed.
Articles Collection (Authors nested within documents)
0 Article Name Some Article
Article Content Some Content
Article Date 20-Feb-2010
Authors 0 Author Name Classy Betty
Author DOB 03-Jan-1970
1 Author Name Casual Sam
Author DOB 04-Mar-1960
1 Article Name Other Article
Article Content Other Content
Article Date 10-Nov-2019
Authors 0 Author Name Casual Sam
Author DOB 04-Mar-1960
2 Article Name Another Article
Article Content Another Content
Article Date 15-Sep-2011
Authors 0 Author Name Classy Betty
Author DOB 03-Jan-1970
1 Author Name Casual Sam
Author DOB 04-Mar-1960
Document DB (no-SQL)
 The same example from previous
slide is designed with one level
nesting in this structure.
 The structure shows Article
structures nested in Author
structures.
 Redundancy in article information,
but that is normal in view of faster
access.
 The nested modelling is predefined
in view of the consumer application.
 Unlike relational DB, unique
identifier not needed.
Authors Collection (Articles nested within documents)
0 Author Name Classy Betty
Author DOB 03-Jan-1970
Articles 0 Article Name Some Article
Article Content Some Content
Article Date 20-Feb-2010
1 Article Name Another Article
Article Content Another Content
Article Date 15-Sep-2011
1 Author Name Casual Sam
Author DOB 04-Mar-1960
Articles 0 Article Name Some Article
Article Content Some Content
Article Date 20-Feb-2010
1 Article Name Other Article
Article Content Other Content
Article Date 10-Nov-2019
2 Article Name Another Article
Article Content Another Content
Article Date 15-Sep-2011
Document DB (no-SQL)
 The same example from previous
slide is designed in JSON structure
following the two modelling
approaches (partially displayed).
[
{
"Article Name": "Some Article",
"Article Content": "Some Content",
"Article Date": "20-Feb-2010",
"Authors": [
{
"Author Name": "Classy Betty",
"Author DOB": "03-Jan-1970"
},
{
"Author Name": "Casual Sam",
"Author DOB": "04-Mar-1960"
}
]
},
{
"Article Name": "Other Article",
"Article Content": "Other Content",
"Article Date": "10-Nov-2019",
"Authors": [
{
"Author Name": "Casual Sam",
"Author DOB": "04-Mar-1960"
}
]
},
…………………………….
]
[
{
"Author Name": "Classy Betty",
"Author DOB": "03-Jan-1970",
"Articles": [
{
"Article Name": "Some Article",
"Article Content": "Some Content",
"Article Date": "20-Feb-2010"
},
{
"Article Name": "Another Article",
"Article Content": "Another Content",
"Article Date": "15-Sep-2011"
}
]
},
{
"Author Name": "Casual Sam",
"Author DOB": "04-Mar-1960",
"Articles": [
{
"Article Name": "Some Article",
"Article Content": "Some Content",
"Article Date": "20-Feb-2010"
},
…………………………….
]
}
]
Graph DB
 This example has many to many
mapping, explained as relations.
 Normalized Structure, no
redundancy.
 Graph consists of nodes and
relationship.
 Both nodes and relationship can
have additional properties.
Type Command
Articles
(Node)
CREATE
(ar1:Article {name:'Some Article',content:"Some Content",date:"20-Feb-2010"})
CREATE
(ar2:Article {name:'Other Article',content:"Other Content",date:"10-Nov-2019"})
CREATE
(ar3:Article {name:'Another Article',content:"Another Content",date:"15-Sep-2011"})
Authors
(Node)
CREATE (au1:Author {name:'Classy Betty',dob:'03-Jan-1970'})
CREATE (au2:Author {name:'Casual Sam',dob:'04-Mar-1960'})
Authored By
(Relationship)
CREATE (ar1)-[:AUTHORED_BY]->(au1)
CREATE (ar1)-[:AUTHORED_BY]->(au2)
CREATE (ar2)-[:AUTHORED_BY]->(au2)
CREATE (ar3)-[:AUTHORED_BY]->(au1)
CREATE (ar3)-[:AUTHORED_BY]->(au2)

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Comparing databases with examples

  • 1. Relational DB vs Document (no-SQL) DB vs Graph DB Explanation through Examples
  • 2. Relational DB  This example has one to one mapping.  Foreign key reference.  Normalized Structure, no redundancy.  Unique identifier necessary for primary key as well as foreign key. Article ID Article Name Article Content Article Date Author ID ar1 Some Article Some Content 20-Feb-2010 au1 ar2 Other Article Other Content 10-Nov-2019 au2 ar3 Another Article Another Content 15-Sep-2011 au2 Author ID Author Name Author DOB au1 Classy Betty 03-Jan-1970 au2 Casual Sam 04-Mar-1960
  • 3. Document DB (no-SQL)  The same example from previous slide is designed with one level nesting in this structure.  Author structures nested in Article structures.  Redundancy in author information, but that is normal in view of faster access.  Unlike relational DB, unique identifier not needed.  Usually represented as JSON structure (illustrated to the right) or key-value store (illustrated in a later slide). [ { "Article Name": "Some Article", "Article Content": "Some Content", "Article Date": "20-Feb-2010", "Author": { "Author Name": "Classy Betty", "Author DOB": "03-Jan-1970" } }, { "Article Name": "Other Article", "Article Content": "Other Content", "Article Date": "10-Nov-2019", "Author": { "Author Name": "Casual Sam", "Author DOB": "04-Mar-1960" } }, { "Article Name": "Another Article", "Article Content": "Another Content", "Article Date": "15-Sep-2011", "Author": { "Author Name": "Casual Sam", "Author DOB": "04-Mar-1960" } } ]
  • 4. Graph DB  This example has one to one mapping, explained as relations.  Normalized Structure, no redundancy.  Graph consists of nodes and relationship.  Both nodes and relationship can have additional properties. Type Command Articles (Node) CREATE (ar1:Article {name:'Some Article',content:"Some Content",date:"20-Feb-2010"}) CREATE (ar2:Article {name:'Other Article',content:"Other Content",date:"10-Nov-2019"}) CREATE (ar3:Article {name:'Another Article',content:"Another Content",date:"15-Sep-2011"}) Authors (Node) CREATE (au1:Author {name:'Classy Betty',dob:'03-Jan-1970'}) CREATE (au2:Author {name:'Casual Sam',dob:'04-Mar-1960'}) Authored By (Relationship) CREATE (ar1)-[:AUTHORED_BY]->(au1) CREATE (ar2)-[:AUTHORED_BY]->(au2) CREATE (ar3)-[:AUTHORED_BY]->(au2)
  • 5. Relational DB  This example has many to many relationship.  Foreign key reference in a separate mapping table.  Normalized Structure, no redundancy.  Unique identifier necessary for primary key as well as foreign key. Article ID Article Name Article Content Article Date ar1 Some Article Some Content 20-Feb-2010 ar2 Other Article Other Content 10-Nov-2019 ar3 Another Article Another Content 15-Sep-2011 Author ID Author Name Author DOB au1 Classy Betty 03-Jan-1970 au2 Casual Sam 04-Mar-1960 Author ID Article ID au1 ar1 au2 ar1 au2 ar2 au1 ar3 au2 ar3
  • 6. Document DB (no-SQL)  The same example from previous slide is designed with one level nesting in this structure.  The structure shows Author structures nested in Article structures.  Redundancy in author information, but that is normal in view of faster access.  The nested modelling is predefined in view of the consumer application.  Unlike relational DB, unique identifier not needed. Articles Collection (Authors nested within documents) 0 Article Name Some Article Article Content Some Content Article Date 20-Feb-2010 Authors 0 Author Name Classy Betty Author DOB 03-Jan-1970 1 Author Name Casual Sam Author DOB 04-Mar-1960 1 Article Name Other Article Article Content Other Content Article Date 10-Nov-2019 Authors 0 Author Name Casual Sam Author DOB 04-Mar-1960 2 Article Name Another Article Article Content Another Content Article Date 15-Sep-2011 Authors 0 Author Name Classy Betty Author DOB 03-Jan-1970 1 Author Name Casual Sam Author DOB 04-Mar-1960
  • 7. Document DB (no-SQL)  The same example from previous slide is designed with one level nesting in this structure.  The structure shows Article structures nested in Author structures.  Redundancy in article information, but that is normal in view of faster access.  The nested modelling is predefined in view of the consumer application.  Unlike relational DB, unique identifier not needed. Authors Collection (Articles nested within documents) 0 Author Name Classy Betty Author DOB 03-Jan-1970 Articles 0 Article Name Some Article Article Content Some Content Article Date 20-Feb-2010 1 Article Name Another Article Article Content Another Content Article Date 15-Sep-2011 1 Author Name Casual Sam Author DOB 04-Mar-1960 Articles 0 Article Name Some Article Article Content Some Content Article Date 20-Feb-2010 1 Article Name Other Article Article Content Other Content Article Date 10-Nov-2019 2 Article Name Another Article Article Content Another Content Article Date 15-Sep-2011
  • 8. Document DB (no-SQL)  The same example from previous slide is designed in JSON structure following the two modelling approaches (partially displayed). [ { "Article Name": "Some Article", "Article Content": "Some Content", "Article Date": "20-Feb-2010", "Authors": [ { "Author Name": "Classy Betty", "Author DOB": "03-Jan-1970" }, { "Author Name": "Casual Sam", "Author DOB": "04-Mar-1960" } ] }, { "Article Name": "Other Article", "Article Content": "Other Content", "Article Date": "10-Nov-2019", "Authors": [ { "Author Name": "Casual Sam", "Author DOB": "04-Mar-1960" } ] }, ……………………………. ] [ { "Author Name": "Classy Betty", "Author DOB": "03-Jan-1970", "Articles": [ { "Article Name": "Some Article", "Article Content": "Some Content", "Article Date": "20-Feb-2010" }, { "Article Name": "Another Article", "Article Content": "Another Content", "Article Date": "15-Sep-2011" } ] }, { "Author Name": "Casual Sam", "Author DOB": "04-Mar-1960", "Articles": [ { "Article Name": "Some Article", "Article Content": "Some Content", "Article Date": "20-Feb-2010" }, ……………………………. ] } ]
  • 9. Graph DB  This example has many to many mapping, explained as relations.  Normalized Structure, no redundancy.  Graph consists of nodes and relationship.  Both nodes and relationship can have additional properties. Type Command Articles (Node) CREATE (ar1:Article {name:'Some Article',content:"Some Content",date:"20-Feb-2010"}) CREATE (ar2:Article {name:'Other Article',content:"Other Content",date:"10-Nov-2019"}) CREATE (ar3:Article {name:'Another Article',content:"Another Content",date:"15-Sep-2011"}) Authors (Node) CREATE (au1:Author {name:'Classy Betty',dob:'03-Jan-1970'}) CREATE (au2:Author {name:'Casual Sam',dob:'04-Mar-1960'}) Authored By (Relationship) CREATE (ar1)-[:AUTHORED_BY]->(au1) CREATE (ar1)-[:AUTHORED_BY]->(au2) CREATE (ar2)-[:AUTHORED_BY]->(au2) CREATE (ar3)-[:AUTHORED_BY]->(au1) CREATE (ar3)-[:AUTHORED_BY]->(au2)