Seven Databases In Seven Weeks Homework Assignments

You should learn a programming language every year, as recommended by The Pragmatic Programmer. But if one per year is good, how about Seven Languages in Seven Weeks? In this book you'll get a hands-on tour of Clojure, Haskell, Io, Prolog, Scala, Erlang, and Ruby. Whether or not your favorite language is on that list, you'll broaden your perspective of programming by examiYou should learn a programming language every year, as recommended by The Pragmatic Programmer. But if one per year is good, how about Seven Languages in Seven Weeks? In this book you'll get a hands-on tour of Clojure, Haskell, Io, Prolog, Scala, Erlang, and Ruby. Whether or not your favorite language is on that list, you'll broaden your perspective of programming by examining these languages side-by-side. You'll learn something new from each, and best of all, you'll learn how to learn a language quickly.

Ruby, Io, Prolog, Scala, Erlang, Clojure, Haskell. With Seven Languages in Seven Weeks, by Bruce A. Tate, you'll go beyond the syntax-and beyond the 20-minute tutorial you'll find someplace online. This book has an audacious goal: to present a meaningful exploration of seven languages within a single book. Rather than serve as a complete reference or installation guide, Seven Languages hits what's essential and unique about each language. Moreover, this approach will help teach you how to grok new languages.

For each language, you'll solve a nontrivial problem, using techniques that show off the language's most important features. As the book proceeds, you'll discover the strengths and weaknesses of the languages, while dissecting the process of learning languages quickly--for example, finding the typing and programming models, decision structures, and how you interact with them.

Among this group of seven, you'll explore the most critical programming models of our time. Learn the dynamic typing that makes Ruby, Python, and Perl so flexible and compelling. Understand the underlying prototype system that's at the heart of JavaScript. See how pattern matching in Prolog shaped the development of Scala and Erlang. Discover how pure functional programming in Haskell is different from the Lisp family of languages, including Clojure.

Explore the concurrency techniques that are quickly becoming the backbone of a new generation of Internet applications. Find out how to use Erlang's let-it-crash philosophy for building fault-tolerant systems. Understand the actor model that drives concurrency design in Io and Scala. Learn how Clojure uses versioning to solve some of the most difficult concurrency problems.

It's all here, all in one place. Use the concepts from one language to find creative solutions in another-or discover a language that may become one of your favorites....more

Paperback, 328 pages

Published November 17th 2010 by Pragmatic Bookshelf

Full Table of Contents

Introduction

Q&A with authors Eric Redmond and Jim Wilson:

1. How did you pick the seven databases?

Eric:

We did have some criteria, if not explicit. The databases had to be open source—we didn’t want to cover any databases that would tie readers to a company. We wanted at least one implementation for each of the five database genres (Relational, Key-Value, Columnar, Document, Graph). Then we chose databases that exemplified some general concepts we wanted to cover, like the CAP theorem, or mapreduce. Finally, we chose databases that were good counterpoints to each other—so we chose MongoDB and CouchDB (different ways of implementing document stores). Or we chose Riak because it was a Dynamo (Amazon’s database) implementation to compare to HBase as a BigTable (Google’s database) implementation.

Jim:

Our goal with the book was principally to introduce readers to the field of choices they now have. Our selections were largely in service of that goal. Even so, it was a pretty long and iterative process. We knew that no matter which ones we picked there’d be people asking why we did or didn’t include their favorite. It came down to choosing the genres we wanted to discuss and then picking databases that had the right combination of (A) representing their genre and (B) relative popularity.

For example, we picked PostgreSQL since it sticks very closely to the SQL standard and is relatively less well known than other OSS competitors like MySQL. Similarly, even though both HBase and Cassandra are column-oriented databases, we went with HBase because Cassandra is more of a hybrid that incorporates elements from both the BigTable paper and the Dynamo paper.

2. Databases are rapidly changing. What do you wish you’d included now?

Eric:

There are hundreds of database options, but I’m glad to see that our choices are still going strong a year later. However, if I had to do it over again, I would like to have added a Triplestore (like Mulgara), since the semantic web is slowly popularizing this method of data storage. I also would have liked to spend more time on Neo4j’s Cypher language, or have covered Hadoop in a bit of detail, since analytics is a huge part of data storage.

Jim:

Yes, databases are rapidly changing, in two senses. First, the field of available data storage technology has been seeing an explosion in recent years. More and more different sorts of databases are cropping up to fill in various niche needs. In the other sense, the databases themselves are rapidly evolving. Even between minor version releases, modern NoSQL databases incorporate more and more features in order to claim more of the market and remain competitive. In that regard, there’s a bit of convergence happening and it makes choosing one even harder as there are more that can meet your needs all the time.

I still think the five genres and seven databases we chose satisfy the criteria that we set out to achieve. But there are others I’d like to write about as well. These include some old favorites like SQLite and some databases you might not think of as such, like OpenLDAP and SOLR (an inverted index/search engine).

3. Why did you decide to write this book?

Eric:

Jim and I discussed writing a book like this for quite some time. About a year and a half ago he sent me an email with no body—the subject was “Seven Databases in Seven Weeks?” The title sold me. We both loved Bruce’s “Seven Languages” book, and this seemed the perfect format to explore this emerging field.

Jim:

As early as March of 2010, Eric and I brainstormed about writing a NoSQL book of some kind. At the time there was a lot of buzz around the term, but also a lot of confusion. We thought we could bring some structure to the discussion and educate people who might not be up to speed yet on all the latest developments.

After reading Bruce A. Tate’s Seven Languages in Seven Weeks I thought, “What about Seven Databases?” Eric submitted a proposal and a few weeks later we were off to the races.

4. What do you see as up and coming databases?

Eric:

I’ve become a big fan of Neo4j. It’s one we covered in the book, but in all honesty we chose it because we wanted to explore an open source graph database. But over the past year it’s really come into its own. I really do believe this is the year we’ll see wider adoption of graph databases.

As for ones we did not cover, I think ElasticSearch is clearly gaining traction. OrientDB is also interesting, as it can act as a relational, key-value, document, or a graph database. I think you’ll see more of this multi-genre behavior in the future. And as I hinted at before, Triplestores are gaining a bit of traction, too, though their problem-set greatly overlaps with general graph databases.

Jim:

There are many, of course, but there are at least two that I personally look forward to exploring in more detail: ElasticSearch and doozer.

ElasticSearch is a distributed, peer-based, REST/JSON powered document search engine. Using a distributed Lucene index at its core, ElasticSearch allows REST clients to find documents based on fuzzy criteria. Everyone needs a search engine, and ElasticSearch makes it easy.

doozer is a fast, headless consensus engine. It’s written in the Go programming language by the smart folks at Heroku. doozer is great for storing small blobs of important information that absolutely must be consistent (like cluster configuration metadata), but without a single point of failure.

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