Elasticsearch, if you are also hearing this term for the first time then join aboard. For all those people wondering what is elastic search and why people use it. Stick till the end of this article. An Elasticsearch can be described as a search engine, index, analytics database, etc. Everybody has their own interpretation of this technology. However, based on those explanations and familiarity with the technology you may understand it or may confuse you further. Frankly, all these explanations are true.
Elasticsearch and Elastic Stack (the components grown around the Elasticsearch ecosystem) are being increasingly used in many situations. From collecting and analyzing the business data to being used as a business intelligence tool for visualization and data analysis. Now, you must be curious about Elasticsearch and how it is shaped to become the most popular enterprise search engine out there.
Let’s dive right into the topic then
What is Elasticsearch?
Elasticsearch is a full-text search engine and powerful analytics that stocks data in JSON format. It is an open-source, distributed search and analytics engine that is developed in Java and built on Apache Lucene. At first, Elasticsearch has started as the Lucene open-source search framework scalable version. Later, the horizontal scale Lucene indices ability was added. The core ability of this technology is to process the JSON requests and provide JSON data. Many companies across the world such as Netflix, Adobe, Facebook, etc use this technology. Through this technology, the users can store, analyze and search huge volumes of data fastly in real-time and provide you with answers in roughly milliseconds. It is a fast and scalable option for searching because instead of searching texts it searches the indexes. If your business wants to create an Elasticsearch cluster then you can leverage on Open distro for Elasticsearch Service from Logit.io.
Why use Elasticsearch?
One of the main reasons why major companies use this technology is because it can do full-text searches. Yes! Most of the traditional databases are slow when it comes to the search technique. The advantage of a full-text search is that it will provide the users with the most relevant search results. Whenever you are searching there are chances that there will be typos. Elasticsearch handles typos easily and also knows about the relevancy too. It uses REAL API to write complex queries. Elasticsearch allows the users to combine and perform different kinds of searches be it unstructured, structured, metrics or geo data types. Simply put, the users can retrieve information from any type of data.
Here are a few advantages of using Elasticsearch
Fast and scalable
With Elasticsearch the users can analyze millions of documents fast in real-time. Another interesting thing about Elasticsearch is that it is built to scale. This technology will run smoothly on a cluster that contains hundreds of nodes or any machine. As you see, growing their cluster from a small one to a large one is not hard, all it requires is a bit of planning and design. This technology finds the best matches for all the full-text searches fast because of distributed inverted indices. Even if there are large data sets the search is done fast.
Manages huge amount of data
As you already know that Elasticsearch performs searches fastly. Along with processing your data fast it can also perform huge amounts of data quickly. With Elasticsearch, the users can manage to process huge amounts of data. No matter how large the data sets are or have huge amounts of data they can retrieve information within 10 seconds.
Easy and Direct
Elasticsearch mostly uses JSON for document serialization. This serialization is supported by many programming languages, it has become a standard format used by the NoSQL movement. In Elasticsearch the documents are stored in close proximity making it easier for you to find them. This way it reduces the data reads and increases the response for search results. The JSON serialization makes it simple and easy to read the documents.
Multilingual
Elasticsearch supports multilingual, based on the character ranges it will decide whether they can break on a character or a space. The Elasticsearch comes with an ICU plugin that is predominantly used for tokenizing and indexing multilingual content. The ICU plugin is based on the Lucene implementation of the Unicode text segmentation.
Failover Mechanism
Apart from being extremely fast and scaling extremely well, Elasticsearch has a failover mechanism in place that avoids data loss. People are afraid that they will lose data when a single node fails. With Elasticsearch you don’t have to worry about it as it has a mechanism called replication in place. The replication shards copy the initial shards and they can serve the end-users similar to the primary shards. If there is any trouble while searching the replicate shards will handle the search request as well as all the behind-the-scenes situations of the data so that the end-users have any issues.
Auto completion
The Elasticsearch comes with search-as-you-type or autocompletes functionality. The speciality of this feature is that it provides the users with relevant suggestions while they are typing their query to improve their search precision. The purpose of this functionality is not to correct spelling errors or the did you mean functionality.
No Schema
The Elasticsearch doesn’t require the definitions such as type, index, field, etc before beginning the indexing process. Even if the object is indexed later or a new property is added later it will automatically be included in the mapping definitions.
Wrapping up
Elasticsearch allows the users to find the answer to their searches fastly in real-time. With the help of this technology, the users can do better indexation of their documents. This technology is still evolving and there is still a huge scope of development as new features are being added. Even with the rapid development, the core of this technology is still consistent yielding the faster performance of the search results. As you have made it to the end of this article, hope you have understood all the information you require about Elasticsearch.
