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Emergence of NoSQL Data Stores

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Mapa Mental sobre Emergence of NoSQL Data Stores, criado por Jody Mc Laughlin em 20-01-2015.
Jody Mc Laughlin
Mapa Mental por Jody Mc Laughlin, atualizado more than 1 year ago
Jody Mc Laughlin
Criado por Jody Mc Laughlin quase 12 anos atrás
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Resumo de Recurso

Emergence of NoSQL Data Stores
  1. Relational Database
    1. Not good at handling big data
    2. Relational and OOP databases don't work well together
      1. OOP Basics
        1. Class
          1. Object
          2. Encapsulation, Polymorphism and Inheritance
          3. Object Relational Impedance Mismatch
            1. ORM (Object relational Mapping)
              1. Enterprise Architecture
                1. Integration Approach
                  1. Application Database
                  2. Scalability
                    1. NoSQL Technologies
                      1. neo4J
                        1. CouchDB
                          1. MongoDB
                            1. Cassandra
                            2. Why use NoSQL
                              1. Realtime interaction with users
                                1. Agility, Consistency, performance, scalability
                                  1. Open Source
                                  2. aggregate vs aggregate ingnorant
                                    1. Relational Models are aggregate ignorant
                                      1. relational for same data requires many tables
                                      2. NoSQL sees aggregate as clusters
                                        1. collection of data related to a unit
                                      3. Graph database
                                        1. neo4J
                                          1. Nodes form network
                                            1. Social networking connecting friends
                                        2. Distribution models
                                          1. High read
                                            1. High write
                                            2. Replication and Sharding
                                              1. Sharding
                                                1. Different data across different nodes
                                                2. Replication
                                                  1. same data across different nodes
                                                3. Replication & Master
                                                  1. Traffic only through master for write
                                                    1. inappropriate for high write
                                                  2. Replication Peer to peer
                                                    1. Traffic written to any node
                                                      1. greater resilience
                                                      2. Combining Master/Slave and Sharding
                                                        1. All write through the server
                                                          1. Different nodes have different data
                                                            1. If master fails must know which node to write too
                                                        2. Consistency Locks
                                                          1. Pessimistic
                                                            1. Lock table for editing at beginning of workflow
                                                            2. Optimistic
                                                              1. Verify with server before making changes at end of workflow

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