Comparing databases with examples
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The document compares and contrasts relational databases, document databases, and graph databases. Relational databases use tables with rows and columns, unique identifiers, and relationships represented through foreign keys. Document databases store data in documents with flexible schemas and embed relationships directly in the documents to reduce storage costs at the expense of redundancy. Graph databases organize data as nodes and edges, where nodes and relationships can have properties.
![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"
}
}
]](https://image.slidesharecdn.com/comparingdatabaseswithexamples-200506170227/85/Comparing-databases-with-examples-3-320.jpg)
![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)](https://image.slidesharecdn.com/comparingdatabaseswithexamples-200506170227/85/Comparing-databases-with-examples-4-320.jpg)
![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"
},
…………………………….
]
}
]](https://image.slidesharecdn.com/comparingdatabaseswithexamples-200506170227/85/Comparing-databases-with-examples-8-320.jpg)
![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)](https://image.slidesharecdn.com/comparingdatabaseswithexamples-200506170227/85/Comparing-databases-with-examples-9-320.jpg)
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)