Top Elasticsearch Books
Elasticsearch is a log analytics platform that processes JSON queries and gives you results on search queries. Using this platform, we can process trillions of data requests in milliseconds to obtain, modify, and store data. Now popularly referred to as elastic stack, owing to its array of applications. This makes its features all the more intriguing for curious developers to try their hands on it. Given below is the list of 10 elasticSearch books in no particular order.
Key Features
- The books contain the basics of installing and setting up Elasticsearch and browsing through the entire ELK environment that consists of Elasticsearch, logstash, and Kibana.
- Learn the ropes of aggregations and pre-processing data to transform them into readable, valuable insights using queries and entity relationships.
- Overlays the detailed guide on APM agents, filters on data, and data pipelining concepts to better figure out the dynamic nature of ElasticSearch.
List of 10 Best Elasticsearch Books
| Sr No. | Books | Author | Published | Rating |
| 1 | Elasticsearch A Clear and Concise Reference | Gerardus Blokdyk | 2022 | Amazon: nil Goodreads: nil |
| 2 | Elasticsearch for Hadoop | Vishal Shukla | 2015 | Amazon:5.0 Goodreads:3.0 |
| 3 | Elasticsearch 8. x Cookbook: Over 180 recipes to perform fast, scalable, and reliable searches for your enterprise, 5th Edition | Alberto Paro | 2022 | Amazon: 2.6 Goodreads:3.8 |
| 4 | Machine Learning with the Elastic Stack: Gain valuable insights from your data with Elastic Stack’s machine learning features, 2nd Edition | Rich Collier , Camilla Montonen , Bahaaldine Azarmi | 2017 | Amazon:4.6 Goodreads: 3.56 |
| 5 | Elasticsearch in Action | Radu Gheorghe, Matthew Lee Hinman, Roy Russo | 2015 | Amazon:4.3 Goodreads: 4.0 |
| 6 | Learning Kibana 7: Build powerful Elastic dashboards with Kibana’s data visualization capabilities, 2nd Edition | Anurag Srivastava and Bahaaldine Azarmi | 2019 | Amazon: 3.8 Goodreads: 4.2 |
| 7 | Applied ELK Stack: Data Insights and Business Metrics With Collective Capability of ElasticSearch, Logstash, and Kibana | Gurpreet Sachdeva | 2017 | Amazon 2.9 Goodreads- 3.0 |
| 8 | Learning elastic stack 7.0 | Pranav Shukla, Sharath Kumar M N | 2017 | Amazon 3.7 Goodreads -4.25 |
| 9 | Kibana 7 Quick Start Guide | Anurag Srivastava | 2019 | Amazon 4.3 Goodreads- 4.67 |
| 10 | Elasticsearch: The Definitive Guide: A Distributed Real-Time Search and Analytics Engine | Clinton Gormley | 2015 | Amazon: 4.3 Goodreads: 4.2 |
Let’s review and discuss the best Elasticsearch books.
Book #1: Elasticsearch A Clear and Concise Reference
Author: Gerardus Blokdyk
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Book Review
Unlike anything you have seen in a guidebook, the book presents an interface. It heavily relies on the questions that arise in your mind and then takes you on a way to identify and obtain the best optimum solution.
Key Takeaways
- Includes case studies and self-assessment techniques to bottom down the areas that could improve.
- Incorporate design practices into elastic search investments for your workspace, whether you are a budding entrepreneur or a consultant.
Book #2: Elasticsearch for Hadoop
Author: Vishal Shukla
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Book Review
Learn full-text search, aggregations, import HDFS, and tackle complex queries in Elasticsearch with apt portions dedicated to each topic. You will also learn how to set up Elasticsearch, Marvel, and Kibana with step-by-step details.
Key Takeaways
- It provides a comprehensive approach to understanding cluster administration better, classifying real-world streaming data, and sorting trends among those.
- Find how Elasticsearch can be mixed with other eco-system tools such as Pig, Hive, and Spark with real-time examples.
Book #3: Elasticsearch 8. x Cookbook: Over 180 recipes to perform fast, scalable, and reliable searches for your enterprise, 5th Edition
Author: Alberto Paro
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Book Review
Get ready to enrich your test palette with delicacies ranging from elastic search functionalities to complex unstructured data. Have a bite of performing index mapping, working with ingest modules, X-pack, and different visualizations while at it.
Key Takeaways
- Get along well with the capabilities of X-pack and execute analytics with text and numeric queries.
- Learn how to install kibana and learn the basics while embarking through advanced mapping.
Book #4: Machine Learning with the Elastic Stack: Gain valuable insights from your data with Elastic Stack’s machine learning features, 2nd Edition
Author: Rich Collier , Camilla Montonen , Bahaaldine Azarmi
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Book Review
Getting the job done by knowing the underlying principles of the concepts used is the best feature of this book. It is filled with intricate details that do not border on monotonous but are there to make learning an enhancive process.
Key Takeaways
- Overlays the underlying principle of analyzing heaps of data effortlessly.
- Integrate elastic machine learning in deploying real-time inference and practice effective detection strategies.
Book #5: Elasticsearch in Action
Author: Radu Gheorghe, Matthew Lee Hinman, Roy Russo
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Book Review
A comprehensive and long book is there to aid you in times of need when thinking of scalable search applications. Look at possible queries and tunings, deploying, backup, and database maintenance explained logically.
Key Takeaways
- Understand, analyze, and explore your data with efficiency and relevancy.
- Use elastic search via HTTP and code written in bash for easier access.
- Ideal for developers and IT professionals looking to upscale their knowledge
Book #6: Learning Kibana 7: Build powerful Elastic dashboards with Kibana’s data visualization capabilities, 2nd Edition
Author: Anurag Srivastava and Bahaaldine Azarmi
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Book Review
This book can be considered the best of both worlds as it portrays the elastic search through data input and storing and kibana through the help of analysis and visuals. A practical guide to knowing the best methods of implementing knowledge in a crisp and easy-to-follow methodology.
Key Takeaways
- Get your hands dirty with several technologies such as Dev Tools, Graphs, spaces, etc.
- Covers various machine learning applications such as processing time-series data using timelion or incorporating kibana into your web apps, APM servers, etc.
Book #7: Applied ELK Stack: Data Insights and Business Metrics with Collective Capability of Elasticsearch, Logstash, and Kibana 1st Edition
Author: Gurpreet Sachdeva
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Book Review
Build a robust architecture with the help of ELK by knowing the basic foundation of ELK implementation in your tech stack. Covers the entire environment analogy of ELK and important aspects of the subject matter.
Key Takeaways
- Familiarize yourself with key aspects of shipping, filtering, and parsing with different components of logstash.
- Process real-time streaming data and tweak them to make them functional insights.
Book #8: Learning Elastic Stack 7.0: Distributed search, analytics, and visualization using Elasticsearch, Logstash, Beats, and Kibana, 2nd Edition
Author: Pranav Shukla, Sharath Kumar M N
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Book Review
A no-nonsense book focusing more on the core functionality of elastic search backed with good and relevant examples to clear any remaining doubts. The topics are explained well, and it is a mandate for anyone looking to enter the elasticSearch field.
Key Takeaways
- Discover the potential of Elasticsearch through interactive dashboards, a cloud-based production environment, and reporting capabilities.
- Create a data pipeline for transferring data from various sources and configure its detailed architecture.
Book #9: Kibana 7 Quick Start Guide
Author: Anurag Srivastava
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Book Review
An insightful and helpful book, as termed by many, is here to make you feel at ease with its constant supply of imperative points relating to RDBMS data, system metrics data, configuring log stash, creating ML jobs, etc.
Key Takeaways
- Have the gripping knowledge of APM through APM agents in this refreshing read
- Curate advanced tools in kibana and practice them on data through exploratory and visual analysis
Book #10: Elasticsearch: The Definitive Guide – A Distributed Real-Time Search and Analytics Engine (Greyscale Indian Edition)
Author: Clinton Gormley
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Book Review
An incredibly well-written manual that encompasses the entirety of elastic search -be it from installing to getting the search engine up and running to get accurate and brilliant data search results. Dive deep into the practice-oriented chapters with enough examples to get you covered.
Key Takeaways
- Learn how to get data in and out with the distributive approach taken by Elasticsearch.
- Deal with generating queries on human language by assimilating aggregations and fuzzy matching.
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