1889669
Mind Map by Jody Mc Laughlin, updated more than 1 year ago
|
|
Created by Jody Mc Laughlin
about 5 years ago
|
|
0
Description
Resource summary
Emergence of NoSQL Data Stores
1 Relational Database
1.1 Not good at handling big data
2 Relational and OOP
databases don't work
well together
3 OOP Basics
3.1 Class
3.1.1 Object
3.2 Encapsulation,
Polymorphism and
Inheritance
4 Object Relational Impedance Mismatch
5 ORM (Object relational Mapping)
6 Enterprise Architecture
6.1 Integration Approach
6.2 Application Database
7 Scalability
8 NoSQL Technologies
8.1 neo4J
8.2 CouchDB
8.3 MongoDB
8.4 Cassandra
9 Why use NoSQL
9.1 Realtime interaction with users
9.2 Agility, Consistency, performance, scalability
9.3 Open Source
10 aggregate vs aggregate ingnorant
10.1 Relational Models are aggregate ignorant
10.1.1 relational for same data requires many tables
10.2 NoSQL sees aggregate as clusters
10.2.1 collection of data related to a unit
11 Graph database
11.1 neo4J
11.1.1 Nodes form network
11.1.1.1 Social networking connecting friends
12 Distribution models
12.1 High read
12.2 High write
13 Replication and Sharding
13.1 Sharding
13.1.1 Different data across different nodes
13.2 Replication
13.2.1 same data across
different nodes
14 Replication & Master
14.1 Traffic only through
master for write
14.1.1 inappropriate for high write
15 Replication Peer to peer
15.1 Traffic written to any node
15.2 greater resilience
16 Combining Master/Slave and Sharding
16.1 All write through the server
16.1.1 Different nodes have different data
16.1.1.1 If master fails must know
which node to write too
17 Consistency Locks
17.1 Pessimistic
17.1.1 Lock table for editing at
beginning of workflow
17.2 Optimistic
17.2.1 Verify with server before making changes at
end of workflow