User-Based Dataedit

Often, users start using Elasticsearch because they need to add full-text search or analytics to an existing application. They create a single index that holds all of their documents. Gradually, others in the company realize how much benefit Elasticsearch brings, and they want to add their data to Elasticsearch as well.

Fortunately, Elasticsearch supports multitenancy so each new user can have her own index in the same cluster. Occasionally, somebody will want to search across the documents for all users, which they can do by searching across all indices, but most of the time, users are interested in only their own documents.

Some users have more documents than others, and some users will have heavier search loads than others, so the ability to specify the number of primary shards and replica shards that each index should have fits well with the index-per-user model. Similarly, busier indices can be allocated to stronger boxes with shard allocation filtering. (See Migrate Old Indices.)


Don’t just use the default number of primary shards for every index. Think about how much data that index needs to hold. It may be that all you need is one shard—any more is a waste of resources.

Most users of Elasticsearch can stop here. A simple index-per-user approach is sufficient for the majority of cases.

In exceptional cases, you may find that you need to support a large number of users, all with similar needs. An example might be hosting a search engine for thousands of email forums. Some forums may have a huge amount of traffic, but the majority of forums are quite small. Dedicating an index with a single shard to a small forum is overkill—a single shard could hold the data for many forums.

What we need is a way to share resources across users, to give the impression that each user has his own index without wasting resources on small users.