Graph Databases, Column Stores, Key Value Stores and Document Databases

Question 1

Relational Database

Answer 1

Primary keys prevent duplication, foreign keys enforce referential integrity and normal form rules prevent anomalies.

Data is always consistent. However performance issues may occur if it is too big and there may be wasted space.

Question 2

Graph Databases

Answer 2

Viewing data as a mathematical graph; relationships between data are key but they do not always need to have the same values. Often used in social networking

Question 3

Advantages of Graph Databases

Answer 3

• Flexible structure
• Clear representation of relationships
• Speed depends on relationships rather than amount of data

Question 4

Disadvantages of Graph Databases

Answer 4

• Difficult to scale as it is a one-tier architecture

- No uniform query language

Question 5

Column Stores

Answer 5

Column stores have tables like relational databases however the data is stored in column rather than rows e.g.
Column 1: (‘Jason’, ‘Steve’)
Column 2: (‘Steggles’, ‘Riddle’)

Question 6

Advantages/Disadvantages of Column Stores

Answer 6

Performance of searching for a specific column is much faster BUT for a specific row is much slower

Question 7

Hashing

Answer 7

Key-Value stores are based on hashing. Applying a hash function to a key to determine where each piece of data is stored in memory

Question 8

Keys

Answer 8

Keys are the raw data which has a hashing function applied to

Question 9

Values

Answer 9

Values can be anything - different databases permit different data types. stored in the key

Question 10

Advantages of Key-Value stores

Answer 10

• Querying is very simple
• Can have a large number of records
• Consistency does not need to be ensured
• Data variation

Question 11

Disadvantages of Key-Value stores

Answer 11

• Lack of referential integrity: can have data in different types
• Basic querying only, can’t do many complex queries

Question 12

Document Databases

Answer 12

Self contained - each document might have different numbers of fields and different fields to other documents.

Similar to key-value stores where there are keys, usually a text string. Document can be queried to return certain parts of it.

Question 13

Representation of Document Databases

Answer 13

Documents might be in a variety of formats, e.g JSON, XML, PDF
Documents are similar to objects in object oriented programming
Basic operations are permitted (CRUD)

Question 14

Advantages of document databases

Answer 14

• Can be good with a variety of data as documents can contain different fields
• Key valued storage approaches offers quick performance

Question 15

Disadvantages of document databases

Answer 15

• Basic operations only
• No normalisation at all; same information can be duplicated in different documents
• Inconsistencies can arise between different documents if the data is entered in incorrectly or updated but not changed in all documents

Question 16

MongoDB

Answer 16

Stores documents in a similar format to JSON with key-value pairs
Uses the concept of Collection which is a collection of documents

Question 17

Collections

Answer 17

Collections store records, which are referred to as documents. Collections are the equivalent of tables in RDBMS, and documents can be thought of as rows in a table. The difference is that you don’t define what columns (or rather attributes) there will be in advance.