Table of Contents for
Seven Databases in Seven Weeks, 2nd Edition

Version ebook / Retour

Cover image for bash Cookbook, 2nd Edition Seven Databases in Seven Weeks, 2nd Edition by Jim Wilson Published by Pragmatic Bookshelf, 2018
  1. Title Page
  2. Seven Databases in Seven Weeks, Second Edition
  3. Seven Databases in Seven Weeks, Second Edition
  4. Seven Databases in Seven Weeks, Second Edition
  5. Seven Databases in Seven Weeks, Second Edition
  6.  Acknowledgments
  7.  Preface
  8. Why a NoSQL Book
  9. Why Seven Databases
  10. What’s in This Book
  11. What This Book Is Not
  12. Code Examples and Conventions
  13. Credits
  14. Online Resources
  15. 1. Introduction
  16. It Starts with a Question
  17. The Genres
  18. Onward and Upward
  19. 2. PostgreSQL
  20. That’s Post-greS-Q-L
  21. Day 1: Relations, CRUD, and Joins
  22. Day 2: Advanced Queries, Code, and Rules
  23. Day 3: Full Text and Multidimensions
  24. Wrap-Up
  25. 3. HBase
  26. Introducing HBase
  27. Day 1: CRUD and Table Administration
  28. Day 2: Working with Big Data
  29. Day 3: Taking It to the Cloud
  30. Wrap-Up
  31. 4. MongoDB
  32. Hu(mongo)us
  33. Day 1: CRUD and Nesting
  34. Day 2: Indexing, Aggregating, Mapreduce
  35. Day 3: Replica Sets, Sharding, GeoSpatial, and GridFS
  36. Wrap-Up
  37. 5. CouchDB
  38. Relaxing on the Couch
  39. Day 1: CRUD, Fauxton, and cURL Redux
  40. Day 2: Creating and Querying Views
  41. Day 3: Advanced Views, Changes API, and Replicating Data
  42. Wrap-Up
  43. 6. Neo4J
  44. Neo4j Is Whiteboard Friendly
  45. Day 1: Graphs, Cypher, and CRUD
  46. Day 2: REST, Indexes, and Algorithms
  47. Day 3: Distributed High Availability
  48. Wrap-Up
  49. 7. DynamoDB
  50. DynamoDB: The “Big Easy” of NoSQL
  51. Day 1: Let’s Go Shopping!
  52. Day 2: Building a Streaming Data Pipeline
  53. Day 3: Building an “Internet of Things” System Around DynamoDB
  54. Wrap-Up
  55. 8. Redis
  56. Data Structure Server Store
  57. Day 1: CRUD and Datatypes
  58. Day 2: Advanced Usage, Distribution
  59. Day 3: Playing with Other Databases
  60. Wrap-Up
  61. 9. Wrapping Up
  62. Genres Redux
  63. Making a Choice
  64. Where Do We Go from Here?
  65. A1. Database Overview Tables
  66. A2. The CAP Theorem
  67. Eventual Consistency
  68. CAP in the Wild
  69. The Latency Trade-Off
  70.  Bibliography
  71. Seven Databases in Seven Weeks, Second Edition

Data Structure Server Store

It can be a bit difficult to classify exactly what Redis is. At a basic level, it’s a key-value store, of course, but that simple label doesn’t really do it justice. Redis supports advanced data structures, though not to the degree that a document-oriented database would. It supports set-based query operations but not with the granularity or type support you’d find in a relational database. And, of course, it’s fast, trading durability for raw speed.

In addition to being an advanced data structure server, Redis can also be used as a blocking queue (or stack) and a publish-subscribe system. It features configurable expiry policies, durability levels, and replication options. All of this makes Redis more of a toolkit of useful data structure algorithms and processes than a member of any specific database genre.

Redis’s expansive list of client libraries makes it a drop-in option for many programming languages. It’s not simply easy to use; it’s a joy. If an API is UX for programmers, then Redis should be in the Museum of Modern Art alongside the Mac Cube.

In Days 1 and 2, we’ll explore Redis’s features, conventions, and configuration. Starting with simple CRUD operations, like always, we’ll quickly move on to more advanced operations involving more powerful data structures: lists, hashes, sets, and sorted sets. We’ll create transactions and manipulate data expiry characteristics. We’ll use Redis to create a simple message queue and explore its publish-subscribe functionality. Then we’ll dive into Redis’s configuration and replication options, learning how to strike an application-appropriate balance between data durability and speed.

Databases are often and increasingly used in concert with each other. Redis is introduced last in this book so that we can use it in just such a manner. In Day 3, we’ll build our capstone system, a rich multidatabase music solution including Redis, CouchDB, Neo4J, and Postgres—using Node.js to cement it together.