Download Database Management

Relational Database Features
Database
Management
Peter Wood
Non-Relational
Databases
Why has the relational model been so successful?
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Data independence
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High level query language - SQL
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Query optimisation
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Support for integrity constraints
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Well-understood database design
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Transaction management and concurrency
Object-oriented
and
object-relational
databases
No SQL databases
Relational Database Limitations
Database
Management
Peter Wood
Non-Relational
Databases
1. all data is value-based - all relationships are
expressed through common values
Object-oriented
and
object-relational
databases
2. data must always be represented in ’flat’ (first normal
form) relations
No SQL databases
3. for some applications, performance is not fast
enough
Relational Database Limitations
Database
Management
Peter Wood
Non-Relational
Databases
1. all data is value-based - all relationships are
expressed through common values
Object-oriented
and
object-relational
databases
2. data must always be represented in ’flat’ (first normal
form) relations
No SQL databases
3. for some applications, performance is not fast
enough
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Limitations 1 and 2 led to the development of
object-oriented and object-relational databases
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Limitations 2 and 3 led to the development of NoSQL
databases
Why might we need Object-Oriented
Databases?
Database
Management
Peter Wood
Non-Relational
Databases
Object-oriented
and
object-relational
databases
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For some applications 1NF is too strict.
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Document management and web site management
Geographic and statistical data
Biological data
...
All these use complex (nested) objects of some form,
where object identity and references help
No SQL databases
Object-Oriented Databases
Database
Management
Peter Wood
Non-Relational
Databases
Support
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object identity
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complex object structures
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classes and inheritance
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object encapsulation (methods for object
manipulation)
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high-level query language (OQL)
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...
Object-oriented
and
object-relational
databases
No SQL databases
Object-Relational Databases
Database
Management
Peter Wood
Object-relational systems (and SQL:1999) add a number
of object-oriented features to relational systems,
including:
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user-defined types
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type inheritance
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table inheritance
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array and multiset types
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object identity
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reference types
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methods
We will consider the first four of these briefly below.
Non-Relational
Databases
Object-oriented
and
object-relational
databases
No SQL databases
Creating User-Defined Types
Database
Management
Peter Wood
Non-Relational
Databases
CREATE TYPE NameType AS (
firstname
varchar(20),
lastname
varchar(20))
FINAL;
CREATE TYPE AddressType AS (
street
varchar(20),
city
varchar(20)
postcode
varchar(8))
NOT FINAL;
FINAL and NOT FINAL relate to subtyping (see later)
Object-oriented
and
object-relational
databases
No SQL databases
Using User-Defined Types
Database
Management
Peter Wood
Non-Relational
Databases
CREATE TABLE person (
name
NameType,
address
AddressType,
dateOfBirth date);
Note that the above table definition uses the user-defined
types NameType and AddressType, along with the built-in
type date
Object-oriented
and
object-relational
databases
No SQL databases
Using User-Defined Types
Database
Management
Peter Wood
Non-Relational
Databases
CREATE TABLE person (
name
NameType,
address
AddressType,
dateOfBirth date);
Note that the above table definition uses the user-defined
types NameType and AddressType, along with the built-in
type date
An SQL example using the above definition is:
SELECT name.firstname, name.lastname FROM person;
Object-oriented
and
object-relational
databases
No SQL databases
Type Inheritance
Database
Management
Peter Wood
CREATE TYPE PersonType (
name
NameType,
address
AddressType)
NOT FINAL;
Non-Relational
Databases
Object-oriented
and
object-relational
databases
No SQL databases
CREATE TYPE StudentType UNDER PersonType (
degree
varchar(20),
department varchar(20))
FINAL;
StudentType is a subtype of PersonType.
NOT FINAL means the type can have subtypes.
FINAL means the type cannot have subtypes.
StudentType inherits the attributes of PersonType.
Table Inheritance
Database
Management
Peter Wood
Non-Relational
Databases
CREATE TABLE person OF PersonType;
CREATE TABLE student OF StudentType UNDER person;
Table student will have all attributes of StudentType
(which includes those of PersonType).
Object-oriented
and
object-relational
databases
No SQL databases
Table Inheritance
Database
Management
Peter Wood
Non-Relational
Databases
CREATE TABLE person OF PersonType;
CREATE TABLE student OF StudentType UNDER person;
Table student will have all attributes of StudentType
(which includes those of PersonType).
Every tuple in student is implicitly also in person, so
SELECT * FROM person
retrieves all person tuples, including student tuples.
Object-oriented
and
object-relational
databases
No SQL databases
Array and Multiset Types
Multiset (a set with possibly duplicate elements) types
were added in SQL:2003.
CREATE TYPE Book AS (
title
varchar(20),
authors
varchar(20) array [10],
keywords
varchar(20) multiset)
NOT FINAL;
CREATE TABLE books OF Book;
Database
Management
Peter Wood
Non-Relational
Databases
Object-oriented
and
object-relational
databases
No SQL databases
Array and Multiset Types
Multiset (a set with possibly duplicate elements) types
were added in SQL:2003.
CREATE TYPE Book AS (
title
varchar(20),
authors
varchar(20) array [10],
keywords
varchar(20) multiset)
NOT FINAL;
CREATE TABLE books OF Book;
INSERT INTO books
VALUES (’Database System Concepts’,
array[’Silberschatz’, ’Korth’, ’Sudarshan’],
multiset[’computer’, ’database’, ’SQL’]);
Database
Management
Peter Wood
Non-Relational
Databases
Object-oriented
and
object-relational
databases
No SQL databases
Array and Multiset Types
Multiset (a set with possibly duplicate elements) types
were added in SQL:2003.
CREATE TYPE Book AS (
title
varchar(20),
authors
varchar(20) array [10],
keywords
varchar(20) multiset)
NOT FINAL;
CREATE TABLE books OF Book;
INSERT INTO books
VALUES (’Database System Concepts’,
array[’Silberschatz’, ’Korth’, ’Sudarshan’],
multiset[’computer’, ’database’, ’SQL’]);
SELECT authors[1] FROM books
WHERE ’database’ IN (UNNEST(keywords));
Database
Management
Peter Wood
Non-Relational
Databases
Object-oriented
and
object-relational
databases
No SQL databases
Database
Management
NoSQL
Peter Wood
Non-Relational
Databases
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NoSQL stands for “Not only SQL”
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Used to refer to various approaches which are
non-relational
These include
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Key-value stores
XML databases
Document stores
Graph databases
Object-oriented
and
object-relational
databases
No SQL databases
NoSQL Systems
Database
Management
Peter Wood
Non-Relational
Databases
Object-oriented
and
object-relational
databases
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Offer scalability and extensibility over
loosely-coupled clusters of commodity hardware.
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As a result, they are often used in large-scale
web-based applications.
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They typically do not offer the extensive transaction
management (ACID) capabilities of RDBMSs.
No SQL databases
Key-value Stores
Database
Management
Peter Wood
Non-Relational
Databases
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Used by Amazon, e.g., for high availability
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see the paper “Dynamo: Amazon’s Highly Available
Key-Value Store” (2007), published in ACM
Symposium on Operating System Principles
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A key-value store enables the storage and retrieval of
values by key.
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It is essentially a big hash table.
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The values are simply sequences of bytes.
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It is up to an application to interpret any logical
structure within the values.
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An example system is Redis (www.redis.io)
Object-oriented
and
object-relational
databases
No SQL databases
XML Databases
Database
Management
Peter Wood
I
Data model is that of XML (elements and attributes).
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XML allows for flexible, nested structures (no
schema is necessary).
Non-Relational
Databases
Object-oriented
and
object-relational
databases
<friends>
No SQL databases
<person>
<name>Alice</name><email>alice@...</email>
</person>
<person>
<name>Bob</name><phone>012...</phone>
</person>
</friends>
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The query language is usually XQuery
(www.w3.org/TR/xquery-30).
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An example system is eXist (www.exist-db.org).
Document Stores
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Database
Management
Peter Wood
Like a key-value store, a document store enables the
Non-Relational
storage and retrieval of values by key.
Databases
In this case, the values do have structure (each is a
Object-oriented
and
“document”).
object-relational
databases
The syntax used for documents is usually JSON
No SQL databases
(JavaScript Object Notation).
{ "friends": [
{ "person":
{ "name": "Alice", "email": "alice@..." }
},
{ "person":
{ "name": "Bob", "phone": "012..." }
}
]
}
An example system is MongoDB
(www.mongodb.org).
Database
Management
Graph Example
Peter Wood
A graph of airports and flight durations:
Non-Relational
Databases
LHR
7
1
2
JFK
Object-oriented
and
object-relational
databases
No SQL databases
MAD
CDG
14
12
8
14
LIM
4
SCL
Nodes represent airports
Edges represent flight connections
e.g., it takes 7 hours to fly between London Heathrow and
JFK (New York)
Graph Databases
Database
Management
Peter Wood
Non-Relational
Databases
I
A graph store represents information in a graph
consisting of nodes and edges.
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Nodes and edges both typically have properties
associated with them.
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Common queries in graphs involve finding
connections (paths) between nodes.
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An example system is Neo4J (www.neo4j.com).
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Neo4J uses its own query language called Cypher.
Object-oriented
and
object-relational
databases
No SQL databases
Summary
Database
Management
Peter Wood
Non-Relational
Databases
I
Performance requirements may force you to adopt a
simpler data model and/or do without ACID
guarantees, e.g.,
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a key-value store
a document store
Object-oriented
and
object-relational
databases
No SQL databases
Summary
Database
Management
Peter Wood
Non-Relational
Databases
I
Performance requirements may force you to adopt a
simpler data model and/or do without ACID
guarantees, e.g.,
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a key-value store
a document store
Complex and/or uncertain data requirements may
suggest a more complex and/or flexible data model is
needed, e.g.,
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object(-relational) database
XML database
graph database
Object-oriented
and
object-relational
databases
No SQL databases