Free Downloads Making Sense Of NoSQL: A Guide For Managers And The Rest Of Us
Summary Making Sense of NoSQL clearly and concisely explains the concepts, features, benefits, potential, and limitations of NoSQL technologies. Using examples and use cases, illustrations, and plain, jargon-free writing, this guide shows how you can effectively assemble a NoSQL solution to replace or augment the traditional RDBMS you have now. About this Book If you want to understand and perhaps start using the new data storage and analysis technologies that go beyond the SQL database model, this book is for you. Written in plain language suitable for technical managers and developers, and using many examples, use cases, and illustrations, this book explains the concepts, features, benefits, potential, and limitations of NoSQL. Making Sense of NoSQL starts by comparing familiar database concepts to the new NoSQL patterns that augment or replace them. Then, you'll explore case studies on big data, search, reliability, and business agility that apply these new patterns to today's business problems. You'll see how NoSQL systems can leverage the resources of modern cloud computing and multiple-CPU data centers. The final chapters show you how to choose the right NoSQL technologies for your own needs. Managers and developers will welcome this lucid overview of the potential and capabilities of NoSQL technologies. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. What's InsideNoSQL data architecture patterns NoSQL for big data Search, high availability, and security Choosing an architectureAbout the Authors Dan McCreary and Ann Kelly lead an independent training and consultancy firm focused on NoSQL solutions and are cofounders of the NoSQL Now! Conference. Table of ContentsPART 1 INTRODUCTION NoSQL: It's about making intelligent choices NoSQL conceptsPART 2 DATABASE PATTERNSFoundational data architecture patternsNoSQL data architecture patternsNative XML databasesPART 3 NOSQL SOLUTIONSUsing NoSQL to manage big dataFinding information with NoSQL searchBuilding high-availability solutions with NoSQLIncreasing agility with NoSQLPART 4 ADVANCED TOPICS NoSQL and functional programming Security: protecting data in your NoSQL systems Selecting the right NoSQL solution
Paperback: 312 pages
Publisher: Manning Publications; 1 edition (September 20, 2013)
Language: English
ISBN-10: 1617291072
ISBN-13: 978-1617291074
Product Dimensions: 7.4 x 0.8 x 9.2 inches
Shipping Weight: 1.2 pounds (View shipping rates and policies)
Average Customer Review: 4.6 out of 5 stars See all reviews (25 customer reviews)
Best Sellers Rank: #404,725 in Books (See Top 100 in Books) #63 in Books > Computers & Technology > Internet & Social Media > Web Browsers #129 in Books > Computers & Technology > Databases & Big Data > Data Warehousing #246 in Books > Computers & Technology > Databases & Big Data > Data Mining
The 'brave new world' or NoSQL databases (DBs) can be confusing: there are various different types of them (graph DBs, column-oriented DBs, key-value stores etc.) and a hotchpotch of vendors (and open-source solutions) - most of which claim that 'their' NoSQL solution is the best - and the answer to all problems.I work as a technical consultant in the database/storage field, and coming from a relational database (RDBMS) background, had been looking for a good resource beyond the non-curated content to be found all over the Internet.I have not been disappointed.(+) The book provides a balanced and informative introduction to the different types/classes of NoSQL DBs(+) I liked the 'jargon buster' approach of the author of actually explaining and defining a lot of the terms used. They did indeed "make sense" of NoSQL from that perspective.(+) I also appreciated the various real-life case studies and use cases for the differing NoSQL DBs, not only taking into account the pure technical side, but also potential business drivers - this is helpful for technical folk like myself whose job entails explaining the pros and cons of DBs to non-technical/business folk who don't appreciate the intricacies of BASE vs. ACID compliance (and probably couldn't case less)(+) Dan McCreary, the author, seems to take a balanced view in the ongoing SQL vs. NoSQL debate, something I missed from some of the other books I've read (like MongoDB in Action, HBase in Action etc.) - no SQL/RDMBS 'bashing' here.(-) My only (ever so small) negative comment would be that the book has not been written for a non-technical/business audience.
As a data geek who has been focused on solving problems with relational databases for a long time and has only casually followed the changes in the industry, Making Sense of NoSQL was a wake-up call. Like many others, I have struggled trying to get my arms around this whole NoSQL thing. Dan McCreary and Ann Kelly’s book helped me see the big picture. As they explain, relational databases are great for certain types of applications but not so great for others. What kinds of applications aren’t they good for?• Processing very large amounts of data. Relational databases are designed to maintain data integrity and consistence, things that are of critical importance to some applications, such as banking, but of far less importance in other applications, such as looking for trends in social networking data. If your bank misses a tenth of a percent of the deposits made in a given day, this is a BIG problem. If you are analyzing, say, Facebook views, and a tenth of a percent of that data is missing, it is very unlikely to impact your results. The problem with maintaining integrity and consistency is that it limits the options for distributing work across multiple processors. And while processing power, disk size and speed, and relational database design have evolved to allow single-processor databases to handle surprisingly large problems, some problems are simply impossible to solve without massive parallelization, something that is difficult to accomplish with relational databases.• Unstructured data (documents, audio, images, and video). Relational databases are great for structured, tabular data, the kind you would put in Excel. Unstructured data is completely different. You know all those emails, Facebook posts, Tweets, etc. we produce each day? All unstructured data.
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