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NoSQL Distilled

(NEU-NoSQL.AP1) / ISBN : 978-1-64459-885-6
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1

Preface

  • Why Are NoSQL Databases Interesting?
  • What’s in the Course
  • Who Should Read This course
  • What Are the Databases
  • Acknowledgments
2

Why NoSQL?

  • The Value of Relational Databases
  • Impedance Mismatch
  • Application and Integration Databases
  • Attack of the Clusters
  • The Emergence of NoSQL
  • Key Points
3

Aggregate Data Models

  • Aggregates
  • Key-Value and Document Data Models
  • Column-Family Stores
  • Summarizing Aggregate-Oriented Databases
  • Further Reading
  • Key Points
4

More Details on Data Models

  • Relationships
  • Graph Databases
  • Schemaless Databases
  • Materialized Views
  • Modeling for Data Access
  • Key Points
5

Distribution Models

  • Single Server
  • Sharding
  • Master-Slave Replication
  • Peer-to-Peer Replication
  • Combining Sharding and Replication
  • Key Points
6

Consistency

  • Update Consistency
  • Read Consistency
  • Relaxing Consistency
  • Relaxing Durability
  • Quorums
  • Further Reading
  • Key Points
7

Version Stamps

  • Business and System Transactions
  • Version Stamps on Multiple Nodes
  • Key Points
8

Map-Reduce

  • Basic Map-Reduce
  • Partitioning and Combining
  • Composing Map-Reduce Calculations
  • Further Reading
  • Key Points
9

Key-Value Databases

  • What Is a Key-Value Store
  • Key-Value Store Features
  • Suitable Use Cases
  • When Not to Use
10

Document Databases

  • What Is a Document Database?
  • Features
  • Suitable Use Cases
  • When Not to Use
11

Column-Family Stores

  • What Is a Column-Family Data Store?
  • Features
  • Suitable Use Cases
  • When Not to Use
12

Graph Databases

  • What Is a Graph Database?
  • Features
  • Suitable Use Cases
  • When Not to Use
13

Schema Migrations

  • Schema Changes
  • Schema Changes in RDBMS
  • Schema Changes in a NoSQL Data Store
  • Further Reading
  • Key Points
14

Polyglot Persistence

  • Disparate Data Storage Needs
  • Polyglot Data Store Usage
  • Service Usage over Direct Data Store Usage
  • Expanding for Better Functionality
  • Choosing the Right Technology
  • Enterprise Concerns with Polyglot Persistence
  • Deployment Complexity
  • Key Points
15

Beyond NoSQL

  • File Systems
  • Event Sourcing
  • Memory Image
  • Version Control
  • XML Databases
  • Object Databases
  • Key Points
16

Choosing Your Database

  • Programmer Productivity
  • Data-Access Performance
  • Sticking with the Default
  • Hedging Your Bets
  • Key Points
  • Final Thoughts

1

Aggregate Data Models

  • Building the Sample Data in MongoDB
2

Key-Value Databases

  • Practicum 1
3

Document Databases

  • Using the find Query in MongoDB
  • Using db.runCommand() in MongoDB
4

Column-Family Stores

  • Practicum 2
  • Creating a Super Column Family in Cassandra
  • Creating a Column Family in Cassandra
  • Inserting and Reading Data in CQL
  • Using the DELETE Query in Cassandra
  • Using the SELECT Command in Cassandra
  • Using the UPDATE Query in Cassandra
5

Graph Databases

  • Practicum 3
  • Indexing Nodes in a Graph in Neo4j
  • Creating a Graph in Neo4j
  • Using the Cypher Query Language
6

Schema Migrations

  • Writing and Reading Document in MongoDB

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