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+<!--
+title: "Change how long Netdata stores metrics"
+description: "With a single configuration change, the Netdata Agent can store days, weeks, or months of metrics at its famous per-second granularity."
+custom_edit_url: https://github.com/netdata/netdata/edit/master/docs/guides/longer-metrics-storage.md
+-->
+
+# Change how long Netdata stores metrics
+
+Netdata helps you collect thousands of system and application metrics every second, but what about storing them for the
+long term?
+
+Many people think Netdata can only store about an hour's worth of real-time metrics, but that's simply not true any
+more. With the right settings, Netdata is quite capable of efficiently storing hours or days worth of historical,
+per-second metrics without having to rely on an [exporting engine](/docs/export/external-databases.md).
+
+This guide gives two options for configuring Netdata to store more metrics. **We recommend the default [database
+engine](#using-the-database-engine)**, but you can stick with or switch to the round-robin database if you prefer.
+
+Let's get started.
+
+## Using the database engine
+
+The database engine uses RAM to store recent metrics while also using a "spill to disk" feature that takes advantage of
+available disk space for long-term metrics storage. This feature of the database engine allows you to store a much
+larger dataset than your system's available RAM.
+
+The database engine is currently the default method of storing metrics, but if you're not sure which database you're
+using, check out your `netdata.conf` file and look for the `memory mode` setting:
+
+```conf
+[global]
+ memory mode = dbengine
+```
+
+If `memory mode` is set to anything but `dbengine`, change it and restart Netdata using the standard command for
+restarting services on your system. You're now using the database engine!
+
+What makes the database engine efficient? While it's structured like a traditional database, the database engine splits
+data between RAM and disk. The database engine caches and indexes data on RAM to keep memory usage low, and then
+compresses older metrics onto disk for long-term storage.
+
+When the Netdata dashboard queries for historical metrics, the database engine will use its cache, stored in RAM, to
+return relevant metrics for visualization in charts.
+
+Now, given that the database engine uses _both_ RAM and disk, there are two other settings to consider: `page cache
+size` and `dbengine multihost disk space`.
+
+```conf
+[global]
+ page cache size = 32
+ dbengine multihost disk space = 256
+```
+
+`page cache size` sets the maximum amount of RAM (in MiB) the database engine will use for caching and indexing.
+`dbengine multihost disk space` sets the maximum disk space (again, in MiB) the database engine will use for storing
+compressed metrics. The default settings retain about two day's worth of metrics on a system collecting 2,000 metrics
+every second.
+
+[**See our database engine
+calculator**](/docs/store/change-metrics-storage.md#calculate-the-system-resources-RAM-disk-space-needed-to-store-metrics)
+to help you correctly set `dbengine multihost disk space` based on your needs. The calculator gives an accurate estimate
+based on how many child nodes you have, how many metrics your Agent collects, and more.
+
+With the database engine active, you can back up your `/var/cache/netdata/dbengine/` folder to another location for
+redundancy.
+
+Now that you know how to switch to the database engine, let's cover the default round-robin database for those who
+aren't ready to make the move.
+
+## Using the round-robin database
+
+In previous versions, Netdata used a round-robin database to store 1 hour of per-second metrics.
+
+To see if you're still using this database, or if you would like to switch to it, open your `netdata.conf` file and see
+if `memory mode` option is set to `save`.
+
+```conf
+[global]
+ memory mode = save
+```
+
+If `memory mode` is set to `save`, then you're using the round-robin database. If so, the `history` option is set to
+`3600`, which is the equivalent to 3,600 seconds, or one hour.
+
+To increase your historical metrics, you can increase `history` to the number of seconds you'd like to store:
+
+```conf
+[global]
+ # 2 hours = 2 * 60 * 60 = 7200 seconds
+ history = 7200
+ # 4 hours = 4 * 60 * 60 = 14440 seconds
+ history = 14440
+ # 24 hours = 24 * 60 * 60 = 86400 seconds
+ history = 86400
+```
+
+And so on.
+
+Next, check to see how many metrics Netdata collects on your system, and how much RAM that uses. Visit the Netdata
+dashboard and look at the bottom-right corner of the interface. You'll find a sentence similar to the following:
+
+> Every second, Netdata collects 1,938 metrics, presents them in 299 charts and monitors them with 81 alarms. Netdata is
+> using 25 MB of memory on **netdata-linux** for 1 hour, 6 minutes and 36 seconds of real-time history.
+
+On this desktop system, using a Ryzen 5 1600 and 16GB of RAM, the round-robin databases uses 25 MB of RAM to store just
+over an hour's worth of data for nearly 2,000 metrics.
+
+To increase the `history` option, you need to edit your `netdata.conf` file and increase the `history` setting. In most
+installations, you'll find it at `/etc/netdata/netdata.conf`, but some operating systems place it at
+`/opt/netdata/etc/netdata/netdata.conf`.
+
+Use `/etc/netdata/edit-config netdata.conf`, or your favorite text editor, to replace `3600` with the number of seconds
+you'd like to store.
+
+You should base this number on two things: How much history you need for your use case, and how much RAM you're willing
+to dedicate to Netdata.
+
+> Take care when you change the `history` option on production systems. Netdata is configured to stop its process if
+> your system starts running out of RAM, but you can never be too careful. Out of memory situations are very bad.
+
+How much RAM will a longer history use? Let's use a little math.
+
+The round-robin database needs 4 bytes for every value Netdata collects. If Netdata collects metrics every second,
+that's 4 bytes, per second, per metric.
+
+```text
+4 bytes * X seconds * Y metrics = RAM usage in bytes
+```
+
+Let's assume your system collects 1,000 metrics per second.
+
+```text
+4 bytes * 3600 seconds * 1,000 metrics = 14400000 bytes = 14.4 MB RAM
+```
+
+With that formula, you can calculate the RAM usage for much larger history settings.
+
+```conf
+# 2 hours at 1,000 metrics per second
+4 bytes * 7200 seconds * 1,000 metrics = 28800000 bytes = 28.8 MB RAM
+# 2 hours at 2,000 metrics per second
+4 bytes * 7200 seconds * 2,000 metrics = 57600000 bytes = 57.6 MB RAM
+# 4 hours at 2,000 metrics per second
+4 bytes * 14440 seconds * 2,000 metrics = 115520000 bytes = 115.52 MB RAM
+# 24 hours at 1,000 metrics per second
+4 bytes * 86400 seconds * 1,000 metrics = 345600000 bytes = 345.6 MB RAM
+```
+
+## What's next?
+
+Now that you have either configured database engine or round-robin database engine to store more metrics, you'll
+probably want to see it in action!
+
+For more information about how to pan charts to view historical metrics, see our documentation on [using
+charts](/web/README.md#using-charts).
+
+And if you'd now like to reduce Netdata's resource usage, view our [performance
+guide](/docs/guides/configure/performance.md) for our best practices on optimization.
+
+[![analytics](https://www.google-analytics.com/collect?v=1&aip=1&t=pageview&_s=1&ds=github&dr=https%3A%2F%2Fgithub.com%2Fnetdata%2Fnetdata&dl=https%3A%2F%2Fmy-netdata.io%2Fgithub%2Fdocs%2Fguides%2Flonger-metrics-storage&_u=MAC~&cid=5792dfd7-8dc4-476b-af31-da2fdb9f93d2&tid=UA-64295674-3)](<>)