---
title: "The Case for Multi-Index Search"
author: "Nick Zadrozny"
date: 2013-02-19
canonical_url: https://bonsai.io/blog/the-case-for-multi-index-search/
license: CC BY-SA 4.0
license_url: https://creativecommons.org/licenses/by-sa/4.0/
copyright: Bonsai.io, 2026
---

## The Case for Multiple Indexes

One of Elasticsearch's biggest strengths is the ease of creating many indexes. It's just a simple HTTP POST, and you're ready to start indexing documents!

##### Example: One index per environment

```sh
curl -X POST http://index.bonsai.io/blog-development
curl -X POST http://index.bonsai.io/blog-staging
curl -X POST http://index.bonsai.io/blog-production
```

Using many indexes for your application is very useful, particularly for scaling. When you have a lot of data, you can use many kinds of natural partitioning points in order to flexibly create many small indexes, which can be easier to scale than a single monolithic index.Some examples of why an app may need many indexes:

-   **Multiple environment** support for keeping your development, staging, production and experimental data isolated.
-   **Multi-tenancy,** in which you create an index per customer in multi-tenant applications.
-   **Temporal sharding,** for applications which process a high volume of updates, particularly when recent documents are more valuable than older documents.
-   **Logical partitioning** between models, to scale one model separately from another. Or within models, to keep related activity closely grouped.
-   **Hot reindexing,** when you need to update your index analysis and mappings settings. Just create a new index and reindex into that in parallel without altering your existing index.

##### Example: Basic three day rolling-window temporal sharding

```sh
curl -X POST http://index.bonsai.io/events-day0
curl -X POST http://index.bonsai.io/events-day1
curl -X POST http://index.bonsai.io/events-day2
```

## Searching Across Indexes

Storing your data into multiple indexes is only as useful as getting your documents back _out_ of those indexes. Toward that end, Elasticsearch has excellent support for multi-index querying. Present since its earliest versions, a multi-index search provides multiple index names in the search request, separated by commas:

##### Multiple-index search with curl

```sh
curl http://index.bonsai.io/authors,articles,comments/_search
```

This is a useful feature for, e.g., the Tire Ruby client, which partitions separate models into their own indexes by default:

##### Multiple index search with Tire

```ruby
Tire.index('authors,articles,comments').search do
  # ...
end
```

## Now Supported on Bonsai

Because of the design of our systems, we don't always support 100% of Elasticsearch's API (see [our new FAQ](https://bonsai.io/faq) for more reasons why). However, as of today, you can now query your indexes with basic multi-index search syntax.

Reserved for future implementation work is the more advanced wildcard and operator syntax, [introduced in Elasticsearch 0.19.8](http://www.elasticsearch.org/blog/2012/07/02/0.19.8-released.html). Both are being worked on with a careful eye on ensuring proper security and privacy of the indexes in our clusters.

If you need this, or any other Elasticsearch feature, [let us know](https://bonsai.io/contact)! We are a small, focused development team and prioritize our plans based on input from our customers.

_Copyright ©️ Bonsai.io, 2026 · By Nick Zadrozny · Originally published at https://bonsai.io/blog/the-case-for-multi-index-search/ · CC BY-SA 4.0_