Paperback: 312 pages
Publisher: Manning Publications; 1 edition (September 20, 2013)
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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