If you take the time to learn Elasticsearch, what you’re really doing is learning a crucial piece of the big data puzzle driving society. Search engines are at the center of everything, governing the way we learn, shop, vote, and behave.
Elasticsearch courses can be your gateway to this exciting technology. In this guide, we explain what Elasticsearch is, how people are using it, and what you can do to get in on the action.
What Is Elasticsearch?
Elasticsearch is an extremely fast and scalable open-source search engine and versatile data analytics tool. Developed in Java and built on the Apache Lucene software library, Elasticsearch is capable of processing large amounts of unstructured information from numerous locations, and it efficiently stores data in the form of JSON documents.
- Career Karma matches you with top tech bootcamps
- Get exclusive scholarships and prep courses
Do you want to learn more about how a coding bootcamp can help you learn to code? Get started by finding the right bootcamp for you along with unlocking additional information about bootcamp cost and reviews.
The storage process is key to its speed and power, which relies on what are called indices. Similar in conceptual terms to a database, an index is a collection of documents that share characteristics. When users submit queries to retrieve documents, they are pulling data from an Elasticsearch index, which is actually a special kind of index called an inverted index.
The inverted structure creates an entry for every unique word used in a set of documents. The result is a highly efficient full-text search function because users can query any word and get back all of the documents in which that word occurs.
On a macro scale, every time you use Elasticsearch for something you are starting a new node, and several nodes connected to one another form a cluster. The significance of a cluster is that data is evenly stored across all clusters, so the number of nodes in the clusters determines how much data is in each node.
That’s all very technical, and it sounds more complicated than it actually is. Let’s leave the abstract behind and explore some concrete applications.
What Is Elasticsearch Used For?
Real-time and scalable search opens doors to various use cases. Anybody who works with data can benefit from Elasticsearch, but in general terms, four of its most common uses are enterprise search, data storage, data analysis, and data modeling.
- Enterprise search. If you have products to sell, the online marketplace is probably a growing part of your business. Elasticsearch can make the search function on your app or website more intuitive, more user-friendly, and more multifaceted.
- Data storage. The scalability of Elasticsearch makes it easy to store large amounts of data. If you’re interested in learning big data, you would be wise to get on board with Elasticsearch.
- Data analysis. Real-time data analytics is Elasticsearch’s bread-and-butter feature. Big companies like Amazon and WalMart have used Elasticsearch to turn raw search data into an instant analysis of consumer spending patterns, seasonal trends, and product performance.
- Data modeling. The distributed nature of Elasticsearch enables users to deploy dynamic mapping to decrease the distance between them and their data. As a result, they can better understand relationships in the data and model the database in big-picture terms, which can help them streamline their organizational practices.
Types of Elasticsearch: Exploring the Elastic Stack
Elasticsearch may be Elastic NV’s flagship product, but it is not the only one that they sell. The other products in the Elastic Stack, formerly called the ELK Stack, provide additional functions for manipulating data in your Elasticsearch-enhanced system.
Kibana is a revelation for those curious about data visualization. Since it was first introduced in 2013, Kibana has been helping users make sense of their Elastic-indexed data with an array of colorful charts, tables, histograms, and other visual aids.
Its machine learning capabilities also check incoming data against patterns in the existing data set, detect anomalies, and inform the user when and why something unexpected happens.
Logstash assists Elasticsearch with data processing. If you deal with data, you know how quickly things can become disorganized, or how having too many data types can jam up the works. Logstash minimizes clutter by streamlining inputs, modifying the overall structure with each new update, and freeing up data to be routed elsewhere.
The recent addition of Beats to the family of Elastic products explains why they changed the name of the ELK Stack (Elasticsearch-Logstash-Kibana Stack) to Elastic Stack.
Beats is one of two Elastic products, along with Logstash, used to facilitate data shipping. Actually seven products in one, each Beat handles the transfer of a different data type and allows users to easily ship whatever data they want from any system to Elasticsearch or Logstash.
Like most great tech innovations, Elasticsearch incorporates a lot of institutional knowledge about data, digital infrastructure, and UI/UX design. And Elasticsearch is so sophisticated and versatile that, even if you get to the point where you can do something specific with it, you might be leaving much of its immense functionality untapped.
To truly learn Elasticsearch, you should be prepared to make a significant commitment of time and resources. Everyone’s learning experience will be different, of course, but we can come up with a general estimate.
How Long Does It Take to Learn Elasticsearch?
If the Elasticsearch courses on the market are any indication, you can learn Elasticsearch from start to finish in just a few days. That being said, many of these courses are designed for people in tech, who have built up a kind of coding muscle memory that makes it easier to add new skills.
If you have no coding experience whatsoever, six months to a year of studying languages like SQL and Java should be sufficient preparation for adding Elasticsearch to your toolbox.
How to Learn Elasticsearch from Scratch: A Step-by-Step Guide
Let’s imagine a small business owner who has intelligence and gumption in spades but very little experience with computers. She heard about Elasticsearch from a friend and thinks it would be great for business. But she never does anything halfway. Before implementing it, she wants to understand the technology backward and forwards.
So, what should she do?
- Gain competency with relational databases. Elasticsearch is basically a turbo-charged relational database. Before sorting out what makes Elasticsearch different and special, you should get to know relational databases and understand how they structure data according to the relational model of data.
- Make your way through the official guide. Now our small business owner is ready to dive into the unique features and vocabulary of Elasticsearch. The Getting Started section is especially valuable for beginners, who can go there for installation tips, querying basics, and an introduction to its full-text search and analytics capabilities.
- Enroll in Elasticsearch courses. The learning process often proceeds in fits and starts without formal coursework to hold students accountable. Their primary value consists in the labs and problem sets that allow students to apply and scale up their learning, which is much harder to do on one’s own.
- Get certified. This step may be desirable for anyone looking to impress investors, customers, or future employers. If you’ve not only digested the knowledge but can claim expertise, you’re a step ahead in the world of business intelligence.
The Best Elasticsearch Courses, Training, and Certifications
Elasticsearch opens doors to the world of data, making storage easier, search engines more powerful, and analytics more adaptive. Like any versatile tool, however, the elasticity of Elasticsearch takes time to get the hang of. Given all the things you can do with the products in the Elastic Stack, it should come as no surprise that the education options are legion.
Whether you want to become a certified Elasticsearch engineer, learn how Elasticsearch stores data and facilitates real-time search, or find out how to incorporate enterprise search into your business, there are courses you can take to make Elasticsearch work for you.
Official Elasticsearch Certification Courses
Offered through the Elasticsearch website, this certification training consists of two courses and prepares students for the Elastic Certified Engineer Exam, which costs $400 to take. Even if you do not intend to take the certification exam, you can enroll in one or both courses to improve your proficiency with Elasticsearch.
Elasticsearch Engineer I
- Instruction Method: Virtual or On-Demand
- Time: 16 hours
- Prerequisites: None
- Cost: $1,600
Available in four 4-hour installments or two 8-hour installments, Elasticsearch Engineer I covers the fundamentals of this versatile tool and consists of six lessons, each of which culminates in a hands-on lab.
By the end of the course, you will know how to write Elasticsearch queries, manage Elasticsearch clusters, and troubleshoot any issues you encounter along the way.
Elasticsearch Engineer II
- Instruction Method: Virtual or On-Demand
- Time: 16 hours
- Prerequisites: Elasticsearch Engineer I or equivalent
- Cost: $1,600
Elasticsearch Engineer II caters to experienced Elasticsearch users and is available in all the same delivery methods as the first course in the series. The sky’s the limit once you’ve unlocked the secrets behind Elasticsearch’s mind-blowing scalability and worked your way through all of this course’s protocols for optimizing your cluster.
Best Online Elasticsearch Courses
Certification is, of course, not the only viable pathway for learning how you can take advantage of the Elasticsearch service. Below are a couple of the more affordable training options that still manage to cover all the essential topics.
- Course Name: Complete Guide to Elasticsearch
- Time: 12 hours
- Prerequisites: Knowledge of JSON
- Cost: $109.99
This course teaches developers everything they need from the Elasticsearch toolbox to build powerful search engines from the ground up. Divided into 13 modules and packaged in over 100 digestible video lectures, it promises a solid foundation in Elasticsearch while paving the way for working with Logstash and Kibana.
The instructor Bo Anderson is a committed teacher with an industry background. He backs up every theoretical concept with a practical lesson so that students fully understand every type of query, including full-text searches.
- Course Name: Elasticsearch Essential Training
- Time: Self-paced
- Cost: $49.99 after free trial
Learn at your own speed with Ben Sullins, a data expert with years of experience coaching companies like Facebook and Microsoft on various business solutions. In six short lessons, Sullins explains how Elasticsearch works and dives into its applications for data architecture. The final lesson focuses on data visualization techniques using Kibana.
Free Elasticsearch Training
Free training opportunities in Elasticsearch seldom come with the same advantages as full courses, but they can be great appetizers nonetheless. What the guides and tutorials below lack in carefully curated course material, they make up for with openness and positivity.
Most of the knowledge is available to the public. If you have a can-do attitude, there’s nothing stopping you from reaching out and seizing the information.
- Course Name: Quick Starts and Fundamentals Training
- Time: Self-paced
- Prerequisites: None
- Cost: FREE
Elastic obviously wants you to buy their stuff. And it’s in their best interest to make their products as user-friendly as possible. Their proprietary video tutorials cover the basics of logging, metrics, searching, and they have free fundamentals training for the entire suite of Elastic Stack products.
The only catch is that, if you want access to the hands-on lab exercises, you either need to sign up for a 14-day free trial or buy the products outright.
- Course Name: Getting Started with Elasticsearch
- Time: 30 minutes
- Prerequisites: Basic understanding of relational databases
- Cost: FREE
If learning by doing is your thing, perhaps all you need is a little nudge to get you started. This Udemy course sets you on your way with 14 short videos, including an installation guide and the essentials of creating, retrieving, updating, and deleting Elasticsearch documents.
Best Elasticsearch Books
A formal course is great, but there’s nothing wrong with the old-fashioned method. It’s always preferable to have knowledge on a given subject at one’s fingertips, and with a book, that’s literally true.
Especially if you plan to use Elasticsearch over the long term, you’ll be proud to have your very own copy of a reference book that you can take down from the shelf as you please.
Elasticsearch: The Definitive Guide, Clinton Gormley and Zachary Tong (2015)
This book contains everything you ever wanted to know about Elasticsearch, packed into 724 informative pages. The best part is that both beginners and more experienced users will find something for them, whether it’s first principles or advanced topics.
Written by two of its earliest users, Elasticsearch: The Definitive Guide approaches the topic with an authoritative eye toward explaining what makes Elasticsearch such an elastic tool for dealing with data.
Relevant Search: With Applications for Solr and Elasticsearch, Doug Turnbull and John Berryman (2016)
Though we often take search engines for granted, they remain a frustrating puzzle for most developers. How can they possibly parse all the intricacies of human speech and anticipate what users mean by a given search term?
That’s where relevance comes in. In this book, Turnbull and Berryman explain how you can use the data modeling functionality of Elasticsearch to return search results that users actually want and improve the overall quality of your enterprise search product.
Best Online Elasticsearch Resources
After you’ve taken Elasticsearch for your first spin, you’ll want to do everything you can to take in your newfound knowledge and skills for regular tune-ups. Refer to the resources below to stay connected to the growing Elasticsearch community.
Elasticsearch Glossary of Terms
The Elasticsearch lexicon can be overwhelming. All of the underlying concepts will be familiar to anyone with a data background, but until you know all the jargon, you might need to consult a glossary from time to time. Keep this page bookmarked and before you know it, you will have the differences between clusters, indexes, and shards committed to memory.
You’ve taken the courses, you’ve read the books, but suddenly you encounter a problem that your training didn’t address. The hivemind over at the Elasticsearch subreddit is here to help answer questions, provide resources, and offer support. And if you ever have the urge to share a success story or simply engage in networking, it’s good for that, too.
Should You Study Elasticsearch?
Elasticsearch has only been around for ten years, but Elastic NV went public in 2017, and the Elastic Stack continues to be a leader in search and analytics innovation. As the huge number of courses, books, and resources on the subject demonstrates, knowledge of Elasticsearch is a valuable asset in the 21st-century economy.
If you work in a field or with a company that you think can benefit from Elasticsearch, you should consider figuring out all that it can do. With Elasticsearch at your side, you may just find yourself getting ahead faster than the time it takes to conduct a real-time search.
About us: Career Karma is a platform designed to help job seekers find, research, and connect with job training programs to advance their careers. Learn about the CK publication.