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

Why a NoSQL Book

What exactly does the term NoSQL even mean? Which types of systems does the term include? How will NoSQL impact the practice of making great software? These were questions we wanted to answer—as much for ourselves as for others.

Looking back more than a half-decade later, the rise of NoSQL isn’t so much buzzworthy as it is an accepted fact. You can still read plenty of articles about NoSQL technologies on HackerNews, TechCrunch, or even WIRED, but the tenor of those articles has changed from starry-eyed prophecy (“NoSQL will change everything!”) to more standard reporting (“check out this new Redis feature!”). NoSQL is now a mainstay and a steadily maturing one at that.

But don’t write a eulogy for relational databases—the “SQL” in “NoSQL”—just yet. Although NoSQL databases have gained significant traction in the technological landscape, it’s still far too early to declare “traditional” relational database models as dead or even dying. From the release of Google’s BigQuery and Spanner to continued rapid development of MySQL, PostgreSQL, and others, relational databases are showing no signs of slowing down. NoSQL hasn’t killed SQL; instead, the galaxy of uses for data has expanded, and both paradigms continue to grow and evolve to keep up with the demand.

So read this book as a guide to powerful, compelling databases with similar worldviews—not as a guide to the “new” way of doing things or as a nail in the coffin of SQL. We’re writing a second edition so that a new generation of data engineers, application developers, and others can get a high-level understanding and deep dive into specific databases in one place.