What is Elasticsearch database? What companies use it?

Can you imagine a search engine focused on the Big Data market? Well, let us tell you that there already is one, and it's called Elasticsearch.

If you are familiar with search engines, you already have a basic idea of what Elasticsearch is, but does it stop there? What makes it different from Google or Bing? 

In order to reach the market, it had to innovate and it’s not for nothing that internationally recognized companies use it today... 

Are you interested in knowing what it is, how it works, who uses it and what it’s for? Then you should read on.

What is Elasticsearch?

Elasticsearch is a distributed, open, and free search and analytics engine that can work with all types of data used in Big Data: textual, numeric, geospatial, structured, and unstructured. 

This search engine was developed based on Apache Lucene and its appearance on the market in 2010 by Elasticsearch N.V. which are now known as Elastic. 

Being RESTful distributed, it has the ability to work with an increasing number of uses, in addition, it offers an incredible speed in data processing. 

How does Elasticsearch work?

Society handles increasing amounts of data, so accessing it can be a complicated task. 

Imagine there is a sea of information and you are looking for something: finding it can be like looking for a needle in a haystack.

This is when Elasticsearch appears as a solution to offer a variety of advantages to those who bet on using such a search engine, which, unlike Google or Bing, will search through a company's data. 

All data that hasn’t been processed will flow into Elasticsearch. It can come from a variety of sources, but here are a few examples:

• Logs on a page.

• System metrics.

• Web applications.

This sample data will be ingested, as this process is known in Elasticsearch, and then parsed, normalized, and finally, enriched before indexing in the Elasticsearch search engine. 

Now that all this data is indexed in Elasticsearch, all users can perform different queries, some more complex than others, and even use aggregations to retrieve summaries of complex data. 

From Kibana all users can create different visualizations to have access to a better overview of the data of their interest, sharing dashboards, and managing the Elasticsearch search engine.

What features does Elasticsearch offer as a search engine?

It’s normal for people to think about Google when hearing the words "search engine”, but Elasticsearch, although it handles the same concept, has a very different application. In fact, that’s where its success comes from. The features it offers are as follows: 

1. Search and analysis

This is one of the best qualities it offers: you can ask Elasticsearch all kinds of questions, which allows you to have a better response capacity.

• Search your way: by allowing you to make different combinations for searches of all the data it stores, you get interesting results. You can ask from simple to complex questions to analyze your results. 

• Analyze on a larger scale: thanks to aggregations, you can get results from a more general view which allows you to explore trends and patterns in the data indexed in the Elasticsearch search engine, a difficult task with a billion log lines.

2. Speed of results

As a good search engine, it can deliver results in a matter of seconds, but it doesn't stop there.

• More breadth: it can cover more ground and still deliver the same speed in search results. 

• Design for improved responsiveness: Thanks to the inverted index working with finite-state transducers, full-text search and BKD trees used for numerical and geographic data storage are more responsive to users. 

• Indexing: This indexing system performed by Elasticsearch is another feature that allows it to offer speed in the Big Data area for data search.

3. Adaptability and scalability

Another of the great advantages offered by Elasticsearch is scalability. Not everyone needs a server with petabytes of data, as this would be a waste of resources for your project and/or company.

To solve this, Elasticsearch offers the adaptability to run your search engine on a laptop or server, giving you scalability that will help you grow with your company or project. 

Elasticsearch scales horizontally to work more efficiently with the number of events per second, while automatically managing how indexes and data searches are distributed across clusters.

4. Relevance capability

Yes, storing data is important, but so is having a good organization based on the needs you may have. This is where Elasticsearch adapts to users by offering different aspects of storage.

• Frequency.

• Age.

• Popularity.

By allowing you to classify your data for searches, you have a better response, offering resistance to possible human errors as Elasticsearch is also prepared to work with these situations.

5. Resilience and flexibility

Elasticsearch does more than just deliver fast results for the data it indexes. Its ability to detect and flag failures help you take action to keep the data in your clusters secure and available for your queries.

In addition to this, the cost of storage is in absolute balance with Elasticsearch, since searches can be done locally or remotely, depending on your needs, which can change from one moment to the next.

What can you use Elasticsearch for?

As we told you before, Elasticsearch is not very strict in the type of data it stores, numeric, text, geographic, structured, or unstructured, it’s really quite versatile and can store all kinds of information, but what use can you give to each of those data?

1. Log monitoring

Elasticsearch is recognized as one of the most comprehensive log data sources in the entire industry, as it’s able to deploy and manage logs at scale as we told you before, from a single computer to a petabyte server.

Thanks to this dynamism you can obtain information on different structured and unstructured logs with the same speed for faster analysis and results, offering real-time solutions, as it detects atypical patterns in its log categorization. 

2. Infrastructure monitoring

The support capability that Elasticsearch has is another reason for its popularity, as it offers support for more than 200 different integrations. Some of the most popular cloud platforms it works with are AWS, Microsoft Azure, and Google Cloud. 

And if that's not enough, it offers you greater ease of monitoring at the infrastructure level and scale, improving visibility into the entire performance which will allow you to identify full stack issues, as well as find "unknown unknowns." 

3. APM

All the applications you have, if integrated with Elasticsearch will offer you deeper visibility, which will help you identify and resolve possible causes of problems that are found and can affect the performance of your application. 

So, you get improved code quality with traceability so you never miss a problem once it's displayed in smart sampling. It will help you quickly identify problems in the application. 

4. Synthetic monitoring

Want to know what the customer journey is and understand the impact the web front-end has on the user experience? You can do this through the synthetic monitoring that Elasticsearch allows you to perform.

You will be able to test user journeys to improve the user experience, as you will also be able to track the availability of your services so that you can verify that you are meeting your SLI and SLO. 

5. Enterprise Search

Growing faster is the goal of hundreds of companies that, thanks to Elasticsearch, can achieve this goal because it offers an open and sophisticated platform that helps improve discovery and growth experiences.

Thanks to this platform you will be able to search databases that allow you to download enterprise systems, e-commerce, and customer support, among others, to access the application or web and find the necessary data faster.

6. Maps

Where? may be the key question to understand for Elastic Stack users to help protect users who rely on Elasticsearch from attackers, and investigate slow response times of applications in certain locations.

Also, it can provide geographic data as it plays an important role in any company's information. Kibana offers a way to weave geospatial layers into temporal data, structured data, and text, among the other types of data it stores.

7. SIEM

The problems that can affect an enterprise change, but through Elasticsearch's Elastic Security for SIEM you can detect, investigate and respond to those changing threats before they become a major problem.

Thanks to the speed of response you can keep your project ahead of the adversity, even when you're taking the next step in scalability to make host-influencing decisions.

8. Endpoint Security

Finally, security. Elasticsearch also offers an endpoint security layer that is capable of preventing ransomware and malware by detecting advanced threats. Not content with this, it also gives the responsible parties contact for an investigation. 

Why should you use the Elasticsearch search engine?

We have already talked about the uses of Elasticsearch, but maybe it’s time to talk about why you should use it.

1. Speed: being developed on Lucene, it offers an excellent full-text search. In addition, it works in real-time, offering a lower latency in the indexing process. 

2. Natural distribution: all data stored in Elasticsearch is distributed in containers known as shards, which generate an automatic copy in case the hardware has an error.

3. Variety of features: although we have already told you about them, these are other reasons why you should go for Elasticsearch. 

4. Simplification of the work process: the whole process of indexing, viewing, and reporting is simplified in the best way for users to have greater ease of use of the tool. 

Now perhaps you have an even more important question: are there well-known companies that are betting on the utilities, features, and uses of Elasticsearch? The answer is a resounding yes. We will mention some of the most important cases.

• Tesco.

• LinkedIn.

• Foursquare.

• Facebook.

• Netflix.

• Dell.

• Ebay.

• Wikipedia.

• The Guardian.

• New York Times.

• Salesforce.

• Docker.

• Orange.

• Groupon.

• Eventbrite.

Considering that Elasticsearch only came to the market in 2010 and has been offering its service for a little more than a decade, it has really earned the respect and use of well-known companies such as those mentioned above.

What do you think about this search engine? 

So far, we’ve seen how the search engine concept can be taken to a completely different area such as Big Data, but for companies. 

Undoubtedly, this concept, in addition to the features and use it offers, has allowed it to become popular, but tell us, do you know another search engine in the Big Data world? Tell us in the comments.