One row in an RDBMS is equivalent to ElasticSearch’s Document. ElasticSearch. Let’s look at an example to help understanding:



“ID” : 1, “Name” : “Shiv”, “Age” : 19, “Gender” : “Male”


In Table 1, the ID of 1 row is identical for JSON data described in JSON. This Json is also known as Document.

In RDBMS When we assign any names for the tables, it’s known as the table’s name. The same applies to Elasticsearch it is called type.

Concept of ElasticSearch

The key concept of Elasticsearch are as follows −

Index in ElasticSearch:-

RDBMS : Database

ElasticSearch : Index

In RDBMS it is databases and the table contains multiple tables. within the table, we have multiple data. Similar to ElasticSearch which is called Index. Index is a different way of looking at data. Index we have multiple types and within the TYPE, we also have JSON. Also, we can say that Index refers to the compilation of documents.

Cluster in ElasticSearch:-

A Cluster is a collection of multiple or single nodes that are combined to store all the information.

Node in ElasticSearch:-

As we all know, Cluster is the result of the combination of Nodes. Each Node is the server that stores the data and also participates in Indexing and Search capabilities.

Shards in ElasticSearch:-

When we create an index and then save the information within it, then it divides the index into multiple buckets which are referred to as Shards. This is because elasticsearch is able to store data in multiple nodes.

Replicas in ElasticSearch:-

ElasticSearch allows us to create replicas or copies of one or more Shards also known as Replicas. We also can provide the names to all of our Replicas.

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