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4 changes: 2 additions & 2 deletions manage-data/data-store/data-streams.md
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# Data streams [data-streams]

A data stream lets you store append-only time series data across multiple indices while giving you a single named resource for requests. Data streams are well-suited for logs, events, metrics, and other continuously generated data.
A data stream acts as a layer of abstraction over a set of indices that are optimized for storing append-only time series data. It stores data across multiple backing indices while giving you a single named resource to use for requests. Data streams are well-suited for logs, events, metrics, and other continuously generated data.

You can submit indexing and search requests directly to a data stream. The stream automatically routes the request to backing indices that store the stream’s data. You can use [{{ilm}} ({{ilm-init}})](../lifecycle/index-lifecycle-management.md) to automate the management of these backing indices. For example, you can use {{ilm-init}} to automatically move older backing indices to less expensive hardware and delete unneeded indices. {{ilm-init}} can help you reduce costs and overhead as your data grows.

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:alt: data streams diagram
:::

A data stream requires a matching [index template](templates.md). The template contains the mappings and settings used to configure the stream’s backing indices.
A data stream requires a matching [index template](templates.md). The template contains the mappings and settings used to configure the stream’s backing indices and defines the {{ilm-init}} policy that the data stream uses.

Every document indexed to a data stream must contain a `@timestamp` field, mapped as a [`date`](elasticsearch://reference/elasticsearch/mapping-reference/date.md) or [`date_nanos`](elasticsearch://reference/elasticsearch/mapping-reference/date_nanos.md) field type. If the index template doesn’t specify a mapping for the `@timestamp` field, {{es}} maps `@timestamp` as a `date` field with default options.

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