[[data-streams]]
= Data streams
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Data streams
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A _data stream_ is a convenient, scalable way to ingest, search, and manage
continuously generated time-series data.
Time-series data, such as logs, tends to grow over time. While storing an entire
time series in a single {es} index is simpler, it is often more efficient and
cost-effective to store large volumes of data across multiple, time-based
indices. Multiple indices let you move indices containing older, less frequently
queried data to less expensive hardware and delete indices when they're no
longer needed, reducing overhead and storage costs.
A data stream is designed to give you the best of both worlds:
* The simplicity of a single named resource you can use for requests
* The storage, scalability, and cost-saving benefits of multiple indices
You can submit indexing and search requests directly to a data stream. The
stream automatically routes the requests to a collection of hidden,
auto-generated indices that store the stream's data.
You can use a <> and
<> to automate the management of
these hidden indices. You can use {ilm-init} to spin up new indices, allocate
indices to different hardware, delete old indices, and take other automatic
actions based on age or size criteria you set. This lets you seamlessly scale
your data storage based on your budget, performance, resiliency, and retention
needs.
[discrete]
[[when-to-use-data-streams]]
== When to use data streams
We recommend using data streams if you:
* Use {es} to ingest, search, and manage large volumes of time-series data
* Want to scale and reduce costs by using {ilm-init} to automate the management
of your indices
* Index large volumes of time-series data in {es} but rarely delete or update
individual documents
[discrete]
[[data-streams-toc]]
== In this section
* <>
* <>
* <>
* <>
include::data-streams-overview.asciidoc[]
include::set-up-a-data-stream.asciidoc[]
include::use-a-data-stream.asciidoc[]
include::change-mappings-and-settings.asciidoc[]