Does your business handle huge amounts of data? Do you have a lot of unstructured data that’s valuable and important to you? Do you want instant search and smart analysis? Does it take long for your client base to receive relevant product information? Do you want to predict business trends and make proactive decisions based on your data? 

So many questions, one simple answer – ElasticSearch. Before we proceed to explain what it is, how it works, and how to determine whether you really need it, it would be useful to explain few other related terms, such as ‘Big Data’.

Before starting to talk about ElasticSearch, we need to explain some other terms. Like Big Data!

Big Data is the term used to describe a large volume of data, both structured and unstructured, which drowns companies every day. The complexity of Big Data is mainly due to a large amount of unstructured data constantly generated by modern systems and technologies, such as weblogs, sensors incorporated in devices, internet searches, social networks (such as Facebook, Twitter, among others), laptops, smartphones, etc.

Illustration of a long code representing big data.

Although the size used to determine whether a given dataset is considered Big Data is not firmly defined and continues to change over time, most analysts currently refer to datasets ranging from 10 Terabytes to several Petabytes.

But what matters is not the amount of data, but what to do with that data. It's important to be able to analyze it in order to identify new opportunities, make better decisions and prepare successful business strategies. That, in turn, leads to smarter business movements, more efficient operations, higher profits, and happier customers. Speed is crucial as well. You need to be able to get the analysis and search results as fast as possible. A week-old report does not help anyone.

Now, let's see how ElasticSearch helps us to achieve all this.

What is ElasticSearch?

In our increasingly complex information society, browsing among tons of information can be really complicated. Nowadays we are more connected than ever. The access to every kind of information now is in just a few clicks.
And although this has endless advantages, it can also be a problem when you searching for exact patterns, among tons of information.

Well, Elasticsearch helps us exactly in this task - to separate the wheat from the chaff, inside this immense barn called Big Data, and show it in a readable and ordered way.

ElasticSearch is an open source, widely distributed, easily scalable,  business search engine, based on Lucene for text search. The searches which support multi-language, geolocation, autocomplete, suggestions are ideal for big data projects. It is based on Java and designed to operate in real time. You can search and index document files in various formats. It was designed to be used in distributed environments by providing flexibility and scalability. Now, ElasticSearch is the most popular business search engine followed by Apache Solr, also based on Lucene.

Person writing on a black board.

Elasticsearch can achieve fast search responses because, instead of searching for the text directly, it looks for an index instead. This is like searching for a keyword by scanning the index on the back of a book, instead of looking for every word on every page of the book. ElasticSearch can scale up to thousands of servers and accommodate petabytes of data. Its enormous capacity results directly from its elaborate and distributed architecture.

Through a REST API, it can be accessed and extended to support all your business intelligence, big data or business analytics applications.
ElasticSearch has a variety of connectors and plugins that allow you to obtain information from multiple data sources: Log files, databases, operating systems, alert monitoring, etc.

7 advantages of using ElasticSearch

  • Fast: By using distributed inverted indexes, ElasticSearch quickly finds the best matches for our full-text searches, even from huge data sets.
  • Real-time index updates: ElasticSearch index updates, such as adding a new document to the index, usually take a millisecond; This allows ElasticSearch to be used for purposes that need a very quick response time.
  • Cost reduction: ElasticSearch provides significant cost advantages when it comes to storing large amounts of data, not to mention that it can identify more efficient ways of doing business.
  • Data analysis: ElasticSearch allows you to analyze data visually using graphs that will help you get a better understanding of different aspects of your business. Additionally, there are several plugins that will make the task of data analysis simpler and more pleasant.
  • Distribution: ElasticSearch is a distributed system that allows us to work with data of any kind, through a search RESTful API. Its stack allows different types of searches and combines them with one another. It can combine structured and unstructured data, thus enabling us to answer all questions regarding the progress of a business or an application.
  • Being a distributed system, ElasticSearch is able to work on a single computer or across hundreds of servers. In any case, it can handle huge amounts of information.
  • Multitenancy: ElasticSearch, through indexing, allows us to get the information we need directly, without having to go through all the locations where the data is stored. Thanks to the use of indexes, this tool shows us the data according to different groupings or criteria, or independently.
  • This tool will help you optimize the data architecture of your company.

The ecosystem of technologies

ElasticSearch is part of a group of technologies (Elastic) that work together and can collaborate when needed:

Illustrative representation of the elastic ecosystem.


  1. ElasticSearch – or the protagonist of this article.
  2. Kibana shapes the data through a visual user interface, allowing you to view and manage the reports.
  3. Logstash is a system of data recovery of logs of all kinds, extensible by means of plugins, and that makes it compatible with any source of information regardless of the format.
  4. Beats is an information loading platform, capable of communicating data between Logstash and ElasticSearch.
  5. ECE (Elastic Cloud Enterprise) allows you to run ElasticSearch and Kibana in the cloud
  6. Logging is an open source logging platform
  7. Metrics enriches your analyses, streamlines your workflows, and simplifies your architecture.
  8. APM provides insight from your application performance.
  9. Site Search offers the opportunity to easily create a great search experience for your site.
  10. Security gives enables you to deal with the latest attack vectors and prevent them from harming your system.

ElasticSearch is a super powerful tool which can upgrade your application and allow you to extract a lot more value from your stored data. Even if it is an application with a low level of data, it is still a good idea to employ this data engine. In fact, with its utilities and all its functions, ElasticSearch provides a complete package in terms of data management.

Check our use case for the Elastic Search Cluster that we created for Clipit.