An index is a collection of documents that should be grouped together for a common reason. For example, you may store all your products in a products index, while all your sales transactions go in sales. Although it is possible to store unrelated data together in a single index, it is often considered an anti-pattern.

We cover how to create and manage indices ourselves in Index Management, but for now we will let Elasticsearch create the index for us. All we have to do is choose an index name. This name must be lowercase, cannot begin with an underscore, and cannot contain commas. Let’s use website as our index name.

Data may be grouped loosely together in an index, but often there are sub-partitions inside that data which may be useful to explicitly define. For example, all your products may go inside a single index. But you have different categories of products, such as "electronics", "kitchen" and "lawn-care".

The documents all share an identical (or very similar) schema: they have a title, description, product code, price. They just happen to belong to sub-categories under the umbrella of "Products".

Elasticsearch exposes a feature called types which allows you to logically partition data inside of an index. Documents in different types may have different fields, but it is best if they are highly similar. We’ll talk more about the restrictions and applications of types in Types and Mappings.

A _type name can be lowercase or uppercase, but shouldn’t begin with an underscore or period. It also may not contain commas, and is limited to a length of 256 characters. We will use blog for our type name.

The ID is a string that, when combined with the _index and _type, uniquely identifies a document in Elasticsearch. When creating a new document, you can either provide your own _id or let Elasticsearch generate one for you.

There are several other metadata elements, which are presented in Types and Mappings. With the elements listed previously, we are already able to store a document in Elasticsearch and to retrieve it by ID—​in other words, to use Elasticsearch as a document store.