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2 changes: 1 addition & 1 deletion docs/user_guide/storing/first_step.md
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# Overview
# Introduction

In the previous sections we saw how to use [`BaseDoc`][docarray.base_doc.doc.BaseDoc], [`DocList`][docarray.array.doc_list.doc_list.DocList] and [`DocVec`][docarray.array.doc_vec.doc_vec.DocVec] to represent multi-modal data and send it over the wire.
In this section we will see how to store and persist this data.
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2 changes: 1 addition & 1 deletion docs/user_guide/storing/first_steps.md
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# Overview
# Introduction

A Document Index lets you store your Documents and search through them using vector similarity.

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6 changes: 3 additions & 3 deletions docs/user_guide/storing/index_elastic.md
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# ElasticSearch Document Index
# Elasticsearch Document Index

DocArray comes with two Document Indexes for [Elasticsearch](https://www.elastic.co/elasticsearch/):

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The following examples is based on [ElasticDocIndex][docarray.index.backends.elastic.ElasticDocIndex],
but will also work for [ElasticV7DocIndex][docarray.index.backends.elasticv7.ElasticV7DocIndex].

# Start ElasticSearch
# Start Elasticsearch

You can use docker-compose to create a local Elasticsearch service with the following `docker-compose.yml`.

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```

You can pass the above as a keyword arguments the `configure()` method or pass an entire configuration object.
To see how, see [here](first_steps.md#configuration-options#customize-configurations).
To see how, see [here](first_steps.md#configuration-options#customize-configurations).