Categories: Persistence

Book Review: “Getting Started with NoSQL” by Gaurav Vaish (Packt Publishing)

Getting Started with NoSQL” is a new book by PACKT PUBLISHING. It gives an introduction to different NoSQL concepts and products. Besides, it explains the differences to SQL databases and when to use which one.

First, the book defines NoSQL and explains what it is and what it is not. Especially, the characteristics and differences compared to SQL are described. The next chapter explains most important NoSQL storage types: Column-oriented databases, document stores, key-value stores, and graph databases. Advantages and disadvantages of these concepts are explained in detail, before comparing most important NoSQL products such as Cassandra, Neo4j, MongoDB or Redis. A case study (which uses MongoDB) concludes the book to show how an implementation with a NoSQL database is different from using a relational database.

What I was missing in this book is a section about other NoSQL concepts such as XML databases or file-based storages such as HDFS (Hadoop Distributed File System).

With 150 pages, the book is not extensive, but sufficient. It is a good introduction to NoSQL databases for developers, architects and decision makers. If you dot not have any experiences with NoSQL databases, then this book is for you. If you are already familiar with different NoSQL concepts and products, you will not learn much new stuff, as the book is not going into deep details. Though, it is still a good overview for NoSQL concepts and products.

 

Best regards,

Kai Wähner (Twitter: @KaiWaehner)

Kai Waehner

bridging the gap between technical innovation and business value for real-time data streaming, processing and analytics

Share
Published by
Kai Waehner

Recent Posts

Virta’s Electric Vehicle (EV) Charging Platform with Real-Time Data Streaming: Scalability for Large Charging Businesses

The rise of Electric Vehicles (EVs) demands a scalable, efficient charging network—but challenges like fluctuating…

3 hours ago

Apache Kafka 4.0: The Business Case for Scaling Data Streaming Enterprise-Wide

Apache Kafka 4.0 represents a major milestone in the evolution of real-time data infrastructure. Used…

3 days ago

How Apache Kafka and Flink Power Event-Driven Agentic AI in Real Time

Agentic AI marks a major evolution in artificial intelligence—shifting from passive analytics to autonomous, goal-driven…

1 week ago

Shift Left Architecture at Siemens: Real-Time Innovation in Manufacturing and Logistics with Data Streaming

Industrial enterprises face increasing pressure to move faster, automate more, and adapt to constant change—without…

2 weeks ago

The Importance of Focus: Why Software Vendors Should Specialize Instead of Doing Everything (Example: Data Streaming)

As real-time technologies reshape IT architectures, software vendors face a critical decision: specialize deeply in…

2 weeks ago

The Top 20 Problems with Batch Processing (and How to Fix Them with Data Streaming)

Batch processing introduces delays, complexity, and data quality issues that modern businesses can no longer…

3 weeks ago