Making Sense of NoSQL
A Guide for Managers and the Rest of Us
Dan McCreary and Ann Kelly
(Manning, paperback)
This is NOT a how-to guide for learning to use NoSQL software and build NoSQL databases. It is a meaty, well-structured overview aimed primarily at “technical managers, [software] architects, and developers.” However, it also is written to appeal to other, not-so-technical readers who are curious about NoSQL databases and where NoSQL could fit into the Big Data picture for their business, institution, or organization.
Making Sense of NoSQL definitely lives up to its subtitle: “A guide for managers and the rest of us.”
Many executives, managers, consultants and others today are dealing with expensive questions related to Big Data, primarily how it affects their current databases, database management systems, and the employees and contractors who maintain them. A variety of problems can fall upon those who operate and update big relational (SQL) databases and their huge arrays of servers pieced together over years or decades.
The authors, Dan McCreary and Ann Kelly, are strong proponents, obviously, of the NoSQL approach. It offers, they note, “many ways to allow you to grow your database without ever having to shut down your servers.” However, they also realize that NoSQL may not a good, nor affordable, choice in many situations. Indeed, a blending of SQL and NoSQL systems may be a better choice. Or, making changes from SQL to NoSQL may not be financially feasible at all. So they have structured their book into four parts that attempt to help readers “objectively evaluate SQL and NoSQL database systems to see which business problems they solve.”
Part 1 provides an overview of NoSQL, its history, and its potential business benefits. Part 2 focuses on “database patterns,” including “legacy database patterns (which most solution architects are familiar with), NoSQL patterns, and native XML databases.” Part 3 examines “how NoSQL solutions solve the real-world business problems of big data, search, high availability, and agility.” And Part 4 looks at “two advanced topics associated with NoSQL: functional programming and system security.”
McCreary and Kelly observe that “[t]he transition to functional programming requires a paradigm shift away from software designed to control state and toward software that has a focus on independent data transformation.” (Erlang, Scala, and F# are some of the functional languages that they highlight.) And, they contend: “It’s no longer sufficient to design a system that will scale to 2, 4, or 8 core processors. You need to ask if your architecture will scale to 100, 1,000, or even 10,000 processors.”
Meanwhile, various security challenges can arise as a NoSQL database “becomes popular and is used by multiple projects” across “department trust boundaries.”
Computer science students, software developers, and others who are trying to stay knowledgeable about Big Data technology and issues should also consider reading this well-written book.
— Si Dunn
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