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Book Description

Most organizations realize that their future depends on the ability to quickly adapt to constant changes brought on by variable and complex environments. It's become increasingly clear that the core source behind these innovative solutions is data.

Polyglot persistence refers to systems that provide many different types of data storage technologies to deal with this vast variability of data. Applications that need to access data from more than one store have to navigate an array of databases in a complex—and ultimately unsustainable—maze. One solution to this problem is readily available.

In this ebook, consultant Joel Ruisi explains how a multi-model database enables you to take advantage of many different types of data models (and multiple schemas) in a single backend. With a multi-model database, companies can easily centralize, manage, and search all the data the IT system collects. The result is data agility: the ability to adapt to changing environments and serve users what they need when they need it.

Through several detailed use cases, this ebook explains how multi-model databases enable you to:

  • Store and manage multiple heterogeneous data sources
  • Consolidate your data by bringing everything in "as is"
  • Invisibly extend model features from one model to another
  • Take a hybrid approach to analytical and operational data
  • Enhance user search experience, including big data search
  • Conduct queries across data models
  • Offer SQL without relational constraints

Table of Contents

  1. 1. Introduction
    1. What’s the Correct Approach?
      1. Here’s What We Have
      2. Integrating Multiple Data Stores
      3. The Multi-Model Database
  2. 2. What Is Agility?
    1. Agility and Data
      1. Being Agile
      2. Dangers of Inflexible IT Systems
      3. What You Lose by Not Being Agile
      4. When Agile Creates New Problems
  3. 3. What Is Multi-Model?
    1. Data Models
      1. Art or Science?
      2. One Model Does Not Fit All
      3. Types of Data and Databases
    2. Advantages of Multi-Model
      1. Pros and Cons of Various Models
      2. When Strong Data Typing Matters
      3. Faster System Implementation
      4. Single Comprehensive Index
      5. Failing Fast
      6. Data Versus Information Versus Knowledge
      7. Enhanced Security
    3. Database Concepts: Consistency, Availability, and Tolerance
      1. ACID versus BASE
      2. Schemas
    4. Additional Benefits of Multiple Models in One Database
      1. Cross-Model Querying
      2. Synergistic Models
  4. 4. Use Cases for Multi-Model
    1. Storing and Managing Multiple Heterogeneous Data Sources
    2. Invisibly Extending Model Features from One Model to Another
    3. A Hybrid Approach to Analytical and Operational Data
    4. Data Consolidation
    5. Enhancing User Search Experience
    6. Adding Search to Big Data
    7. Querying Across Data Models
    8. Offering SQL Without Relational Constraints
    9. Multi-Model Database Storage Types
  5. 5. How Multi-Model Yields Agility
    1. Better Understanding of Your Data
    2. Faster Reaction Time to an Ever-Changing Environment
    3. Cost-Effective Prototyping
    4. Faster Proof of Value
    5. Fail Fast and Move On
  6. 6. Summary
    1. Moving Forward with Multi-Model
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