Prometheus vs InfluxDB

Time-series monitoring is an essential tool for software engineers, data engineers, system administrators, and even for business metrics analysis. However, to effectively monitor time-series data we need servers, databases, visualizations, querying and more. There’s two major service providers out there who have this full functionality: Prometheus and InfluxDB. 

In this article, we will describe and compare Prometheus and InfluxDB, so that readers can choose which one best suits their needs.

Metricfire provides a free trial for Hosted Prometheus for people who are looking to experience Prometheus. You can use it to try Prometheus in practice and even make some awesome Grafana dashboards right on our platform. You can also schedule a demo and talk to us directly about your monitoring questions.

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What is Prometheus?

Prometheus is an open-source monitoring tool and time-series database. Prometheus provides powerful query language, storage, and visualization features for its users. It also has a range of client libraries for simple interaction with it. In addition, Prometheus can be integrated with many other different systems (for example, Docker, StatsD, MySQL, Consul, etc.). 

You can read more about Prometheus and how to build the dashboards in our article about Prometheus Dashboards. As well, you can learn all about Prometheus in our Prometheus Monitoring 101 article, or how to Deploy Prometheus to Kubernetes in our video tutorial. 

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What is InfluxDB?

InfluxDB is an open-source time-series database from the InfluxData company. It is widely used as a system for monitoring applications, infrastructure, and IoT, as well as for data analysis. InfluxDB has its own ecosystem called TICK-stack consisting of four components: Telegraf, InfluxDB, Chronograf, and Kapacitor. InfluxDB is the central component of this stack. Its primary aim is to store data, while Telegraf acts as a data collector, Kapacitor provides tools for real-time data processing (for example, alerting), and Chronograf is the system for visualization and interaction with all other components of the stack.

We've also written an in depth article comparing Chronograf and Grafana on their visualization abilities.

Key similarities between Prometheus and InfluxDB

Both Prometheus and InfluxDB are tools for monitoring and storing time-series data. There are actually a lot of similar features between them. Let’s look at these similarities:

• Both platforms use identical data compression techniques.
  
  
• Both platforms support multi-dimensional data. This is done by using labels in Prometheus and tags in InfluxDB.
  
  
• Both systems have additional instruments to deal with specific tasks. For example, InfluxDB has Kapacitor, and Prometheus has Alertmanager for alerting purposes.
  
  
• They both use query languages to interact with metrics and analyse them.
  
  
• Prometheus, as well as InfluxDB, can be integrated with a lot of different systems. You can explore the list of available for InfluxDB plugins here. As you can see, there are input and output plugins, extensions for cloud integrations and incident management. At the same time, Prometheus integrations and exporters could be accessed here. There are tools for integration with different databases, messaging systems, storages, APIs, other monitoring systems (including InfluxDB), and hardware related integrations, etc.
  
  
• If for some use cases it is not enough to use the existing plugins, the functionality of both systems can be extended with the help of web hooks. In such a way, you can do very specific things, for example, actions automation.
  
  
• Both InfluxDB and Prometheus are open-source, and both have a large community of developers adding to the projects all the time. However Prometheus has 25k+ stargazers on Github, whereas InfluxDB only has 15k+.
  
  
• There are hosted versions of InfluxDB as well as Prometheus. For example, we have Metricfire’s Hosted Prometheus.
  
  

The main similarity between Prometheus and InfluxDB is due to the fact that they both have a similar mission and solve similar tasks (monitoring and time-series data storing).

Key differences between Prometheus and InfluxDB

Let’s now look at what is different between Prometheus and InfluxDB:

• The most notable difference is between the scopes of these platforms. Both systems could be used for monitoring and time-series data storing. However, InfluxDB is more known as a time-series database, while Prometheus has a broader scope of monitoring purposes.
  
  Actually, InfluxDB itself cannot be used for the tasks of data visualization or alerting. We should use other instruments from the TICK-stack: Kapacitor for alerting and Chronograf for visualization. At the same time, Prometheus also needs to use Alertmanager to send notifications, but defining the alerting and recording rules can be done directly in the Prometheus interface. Additionally, Alertmanager provides features for deduplication, grouping, and silencing. Prometheus has many components but they fit together seamlessly.
  
  
• InfluxDB uses its own query language - InfluxQL. It is very similar to the usual SQL, so if you know the latest, there shouldn’t be any problem to create an InfluxQL query. Prometheus provides a functional language for querying called PromQL.
  
  Somebody can consider InfluxQL simpler for people who worked previously with SQL, but PromQL is actually very easy and powerful. It was developed specifically for monitoring purposes, alerting and graphing. It is less wordy than InfluxQL and provides a range of convenient functions. For example, here is how we can compute the mean value of the time-series in InfluxDB:
  
  SELECT MEAN("value") FROM "time_series_name"
  
  At the same time, the same thing can be done in a more brief way with Prometheus in PromQL:
  
  avg(time_series_name)
  
  Here is one more example (selecting all public values from the database):
  
  InfluxDB:SELECT "value" FROM "time_series_name" WHERE tag="public"
  
  Prometheus:time_series_name{labelname="public"}‍
  
  You may like InfluxQL for its similarity with SQL, but Prometheus really provides a very powerful, direct, and convenient language for working with stored data.
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• Prometheus servers, as well as InfluxDB, can be united in clusters to be able to process high load. But Prometheus servers (and servers running the open-source InfluxDB version) are independent of each other by default. This means each server uses its own local resources. When your processing requirements increase, you should take care to set up a cluster of servers (both for Prometheus and InfluxDB).
  
  But the commercial version of InfluxDB is different. It is a distributed cluster solution by default. So, it consists of many nodes that interact together. So, when the load increases, you don’t have to worry about scaling. On the other hand, you will have to manage a complex cluster from the very beginning, which may be difficult. If you don’t need to process high load, it can even be considered redundant. Prometheus and the open-sourced version of InfluxDB are easier to manage if your use case is standard and relatively simple.
  
  Anyway, remember that when you use our Hosted Prometheus solution, you avoid all the headache caused by setting up and maintaining the Prometheus cluster.
  
  
• InfluxDB supports float64, int64, bool, and string data types. The Prometheus’ main data type is float64 (however, it has limited support for strings).
  
  
• Prometheus can write data with the millisecond resolution timestamps. InfluxDB is more advanced in this regard and can work with even nanosecond timestamps.
  
  
• Prometheus uses an append-only file per time-series approach for storing data. InfluxDB uses another method of storing, that is considered better for working with events logging.
  
  
• Prometheus is developed to pull metrics periodically from the target system. Alternatively, InfluxDB expects that an application will be sending data to it. So, when working with InfluxDB, you should set up the target system to push data to the InfluxDB server. For similar situations, you can use Prometheus push gateway in situations where metrics cannot be pulled.
  
  
• Some users report an issue with high consumption of memory and CPU resources by InfluxDB server (when comparing with similar use cases where Prometheus server was used).

Conclusion‍

We can say that while Prometheus and InfluxDB are very similar tools, the main difference between them is that they serve slightly different use cases. Prometheus has a range of features that make it a good instrument for metrics monitoring, graphing, and alerting. 

At the same time, InfluxDB is a database for event logging. The commercial version of InfluxDB can also be a smart choice when you need to process big amounts of data per time unit. This is because commercial InfluxDB can scale horizontally without much additional configuration changes. Hosted Prometheus by MetricFire competes with the commercial InfluxDB option as a service with broad functionality and great visualizations through Grafana. 

In this article, we described two popular platforms for time series data storing and monitoring: Prometheus and InfluxDB. It was focused on the comparison of these solutions and the detection of their similarities and differences.

If you have any questions you can get in touch with us by booking a demo. We can tell you about what Hosted Prometheus can do for you. Don’t forget that you can also use Metricfire’s free 14-day trial to try Hosted Prometheus in action. It’s great to get on the platform to check it out and query some metrics.