SQL vs. NoSQL Databases

SQL vs. NoSQL Databases
Presented By: Osama Jomaa
Miami University

SQL Database Issues
●
Scalability
●
Flexibility

Scalability
The ability of a system to handle a growing amount
of work in a capable manner or its ability to be
enlarged to accommodate that growth.

Scalability Types
Photo Source: https://blog.openshift.com/scaling-in-action-on-openshift/
Vertical Horizontal

SQL Dbs are Vertically Scalable
✔ Low performance
✔ Lots of engineering work
✔ Expensive

Flexibility
The ability of a system to change during
the development life cycle

SQL DBs Structure
✔ Change of the data structure is
difficult and costly
✔ Not suitable for model software
methodologies, e.g. agile.

Performance
The capabilities of a system when
observed under particular conditions

SQL DBs are Relational DBs
✔ Cross-table queries are inevitable
✔ Multiple queries on different tables
hurts the performance
✔ No direct mapping between tables in a
database and objects in an OOL

NoSQL Databases
Not Only SQL :)

Flexibility
✔ Schema-free Database
✔ Suitable for the rapid application
development

Performance
✔ No cross-collection queries
✔ Data is manipulated through
OO APIs

NoSQL Database Types
✔ Document Databases
✔ MongoDB
✔ Graph Stores
✔ Key-value Stores
✔ Wide-column stores

MongoDB
High Performance
✔ Easily Scalable
✔ Document-based
✔ NoSQL
✔ BSON formatted Data
✔ Queried through Idiomatic Drivers

MongoDB
ID First_Name Last_Name
0 Osama Jomaa
1 Steve Brightwood
ID Account_Type Account_Balance Currency Holder (FK:
Persons)
0 Investement 80000.00 USD 0
1 Savings 70400.00 USD 0
2 Checking 4500.00 USD 0
3 Checking 4500.00 YEN 1
4 Investement 5000.00 YEN 1
5 Savings 6000.00 YEN 1
Account Holders
Accounts

MongoDB
ID First_Name Last_Name
0 Osama Jomaa
1 Steve Brightwood
ID Account_Type Account_Balance Currency Holder (FK:
Persons)
0 Investment 80000.00 USD 0
1 Savings 70400.00 USD 0
2 Checking 4500.00 USD 0
3 Checking 4500.00 YEN 1
4 Investment 5000.00 YEN 1
5 Savings 6000.00 YEN 1
Account Holders
Accounts
Table
Record

MongoDB
[{
"ID": 0,
"first_name": "Osama",
"last_name": "Jomaa",
"accounts": [
{
"id": 0,
"account_type": "Investement",
"account_balance": "80000.00",
"currency": "USD"
},
{
"id": 1,
"account_type": "Savings",
"currency": "USD"
},
{
"id": 2,
"account_type": "Checking",
"currency": "USD"
}]
},
{
"ID": 1,
"first_name": "Steve",
"last_name": "Brightwood",
"accounts": [
{
"id": 3,
"currency": "YEN"
},
{
"id": 4,
"currency": "YEN"
},
{
"id": 2,
"currency": "YEN"
}]
}]

MongoDB
[{
"ID": 0,
"first_name": "Osama",
"last_name": "Jomaa",
"accounts": [
{
"id": 0,
"currency": "USD"
},
{
"id": 1,
"currency": "USD"
},
{
"id": 2,
"currency": "USD"
}]
},
{
"ID": 1,
"first_name": "Steve",
"last_name": "Brightwood",
"accounts": [
{
"id": 3,
"currency": "YEN"
},
{
"id": 4,
"currency": "YEN"
},
{
"id": 2,
"currency": "YEN"
}]
}]
Collection
Document
Array

Our DB: Paper
{
“PMID” : The pubmed id for the paper
“Organism” : The organism that the paper studies
“Citation” : The list of citations of the paper
“MeshHeadings” : The list of the MeSH headings that the
paper is annotated to
“PubTypes” : The list of publication types for this paper
“Proteins”: The list of proteins studied in the paper
}

Our DB: Protein
{
“PID”: Protein ID,
“Organism”: The organism of the protein
“Sequence”: The amino acid sequence of the protein
“GO Terms”: The Gene Ontology terms that the proteins
is annotated to
“Papers”: The list of papers that the protein is studied in
“Homologs”: The homologs of the protein acquired by
BLAST
}

Our DB: MeSH Tree
{
“TID”: Term ID
“Category”: One of the 16 MeSH top level categories
“Parent”: The direct MeSH parent of the term
“Ancestors”: The list of the term MeSH ancestors
}

SQL vs. NoSQL Databases

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