Need advice about which tool to choose?Ask the StackShare community!


+ 1

+ 1
Add tool

Prometheus vs StatsD: What are the differences?


Prometheus and StatsD are popular open source monitoring and metrics collection tools used in the field of DevOps. While both tools are geared towards collecting and analyzing metrics data, there are key differences that set them apart.

  1. Data Collection Methodology: Prometheus follows a pull-based model where it actively scrapes the targets at regular intervals to collect data. In contrast, StatsD uses a push-based approach, where applications actively send metrics to a StatsD daemon, which then forwards the data to a backend for storage.

  2. Data Storage and Retrieval: Prometheus stores all scraped metrics in a time-series database with a built-in query language for retrieval and analysis. It provides a long-term storage option and allows for complex queries and aggregations. On the other hand, StatsD does not have its own storage; it relies on a backend such as Graphite or InfluxDB for storage, and queries are typically more limited in functionality.

  3. Metrics Processing: Prometheus provides powerful metric processing capabilities, allowing for calculations, transformations, and alerting based on rules defined in its query language. It supports aggregation, rate calculations, and function application on metrics data. In contrast, StatsD provides less advanced processing capabilities and mainly focuses on metrics aggregation and basic calculations like summing, averaging, and sampling.

  4. Service Discovery: Prometheus has built-in service discovery mechanisms that allow it to automatically discover and monitor new targets using various methods such as DNS, Kubernetes, or EC2 APIs. StatsD does not have built-in service discovery and requires additional configuration for target discovery.

  5. Alerting and Monitoring: Prometheus has a sophisticated alerting system with flexible rules and notification options that can be triggered based on metric thresholds or sophisticated queries. It also provides a web-based console for visualizing and monitoring metrics data. StatsD does not have built-in alerting or web-based monitoring capabilities, and it typically relies on external tools like Graphite or Grafana for visualization and alerting.

  6. Ecosystem and Integrations: Prometheus has a large and active community, with extensive documentation, libraries, and integrations with popular tools like Grafana, Kubernetes, and Docker. StatsD, although widely used, has a slightly smaller ecosystem and fewer integrations available.

In summary, Prometheus and StatsD differ in their data collection methodology, storage and retrieval mechanisms, metrics processing capabilities, service discovery, alerting and monitoring features, and ecosystem and integrations. Each tool has its own strengths and use cases, depending on specific monitoring and metrics requirements.

Advice on Prometheus and StatsD
Susmita Meher
Senior SRE at African Bank · | 4 upvotes · 795.7K views
Needs advice

Looking for a tool which can be used for mainly dashboard purposes, but here are the main requirements:

  • Must be able to get custom data from AS400,
  • Able to display automation test results,
  • System monitoring / Nginx API,
  • Able to get data from 3rd parties DB.

Grafana is almost solving all the problems, except AS400 and no database to get automation test results.

See more
Replies (1)
Sakti Behera
Technical Specialist, Software Engineering at AT&T · | 3 upvotes · 581.1K views

You can look out for Prometheus Instrumentation ( Client Library available in various languages to create the custom metric you need for AS4000 and then Grafana can query the newly instrumented metric to show on the dashboard.

See more
Sunil Chaudhari
Needs advice

Hi, We have a situation, where we are using Prometheus to get system metrics from PCF (Pivotal Cloud Foundry) platform. We send that as time-series data to Cortex via a Prometheus server and built a dashboard using Grafana. There is another pipeline where we need to read metrics from a Linux server using Metricbeat, CPU, memory, and Disk. That will be sent to Elasticsearch and Grafana will pull and show the data in a dashboard.

Is it OK to use Metricbeat for Linux server or can we use Prometheus?

What is the difference in system metrics sent by Metricbeat and Prometheus node exporters?

Regards, Sunil.

See more
Replies (2)
Matthew Rothstein

If you're already using Prometheus for your system metrics, then it seems like standing up Elasticsearch just for Linux host monitoring is excessive. The node_exporter is probably sufficient if you'e looking for standard system metrics.

Another thing to consider is that Metricbeat / ELK use a push model for metrics delivery, whereas Prometheus pulls metrics from each node it is monitoring. Depending on how you manage your network security, opting for one solution over two may make things simpler.

See more

Hi Sunil! Unfortunately, I don´t have much experience with Metricbeat so I can´t advise on the diffs with Prometheus...for Linux server, I encourage you to use Prometheus node exporter and for PCF, I would recommend using the instana tile ( Let me know if you have further questions! Regards Jose

See more
Mat Jovanovic
Head of Cloud at Mats Cloud · | 3 upvotes · 724.7K views
Needs advice

We're looking for a Monitoring and Logging tool. It has to support AWS (mostly 100% serverless, Lambdas, SNS, SQS, API GW, CloudFront, Autora, etc.), as well as Azure and GCP (for now mostly used as pure IaaS, with a lot of cognitive services, and mostly managed DB). Hopefully, something not as expensive as Datadog or New relic, as our SRE team could support the tool inhouse. At the moment, we primarily use CloudWatch for AWS and Pandora for most on-prem.

See more
Replies (2)
Lucas Rincon

this is quite affordable and provides what you seem to be looking for. you can see a whole thing about the APM space here

See more

I worked with Datadog at least one year and my position is that commercial tools like Datadog are the best option to consolidate and analyze your metrics. Obviously, if you can't pay the tool, the best free options are the mix of Prometheus with their Alert Manager and Grafana to visualize (that are complementary not substitutable). But I think that no use a good tool it's finally more expensive that use a not really good implementation of free tools and you will pay also to maintain its.

See more
Decisions about Prometheus and StatsD
Matt Menzenski
Senior Software Engineering Manager at PayIt · | 16 upvotes · 995.7K views

Grafana and Prometheus together, running on Kubernetes , is a powerful combination. These tools are cloud-native and offer a large community and easy integrations. At PayIt we're using exporting Java application metrics using a Dropwizard metrics exporter, and our Node.js services now use the prom-client npm library to serve metrics.

See more
Leonardo Henrique da Paixão
Junior QA Tester at SolarMarket · | 15 upvotes · 360.9K views

The objective of this work was to develop a system to monitor the materials of a production line using IoT technology. Currently, the process of monitoring and replacing parts depends on manual services. For this, load cells, microcontroller, Broker MQTT, Telegraf, InfluxDB, and Grafana were used. It was implemented in a workflow that had the function of collecting sensor data, storing it in a database, and visualizing it in the form of weight and quantity. With these developed solutions, he hopes to contribute to the logistics area, in the replacement and control of materials.

See more
Get Advice from developers at your company using StackShare Enterprise. Sign up for StackShare Enterprise.
Learn More
Pros of Prometheus
Pros of StatsD
  • 47
    Powerful easy to use monitoring
  • 38
    Flexible query language
  • 32
    Dimensional data model
  • 27
  • 23
    Active and responsive community
  • 22
    Extensive integrations
  • 19
    Easy to setup
  • 12
    Beautiful Model and Query language
  • 7
    Easy to extend
  • 6
  • 3
    Written in Go
  • 2
    Good for experimentation
  • 1
    Easy for monitoring
  • 9
    Open source
  • 7
    Single responsibility
  • 5
    Efficient wire format
  • 3
    Handles aggregation
  • 3
    Loads of integrations
  • 1
    Many implementations
  • 1
    Scales well
  • 1
    Simple to use
  • 1

Sign up to add or upvote prosMake informed product decisions

Cons of Prometheus
Cons of StatsD
  • 12
    Just for metrics
  • 6
    Bad UI
  • 6
    Needs monitoring to access metrics endpoints
  • 4
    Not easy to configure and use
  • 3
    Supports only active agents
  • 2
    Written in Go
  • 2
    TLS is quite difficult to understand
  • 2
    Requires multiple applications and tools
  • 1
    Single point of failure
  • 1
    No authentication; cannot be used over Internet

Sign up to add or upvote consMake informed product decisions

- No public GitHub repository available -

What is Prometheus?

Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.

What is StatsD?

It is a network daemon that runs on the Node.js platform and listens for statistics, like counters and timers, sent over UDP or TCP and sends aggregates to one or more pluggable backend services (e.g., Graphite).

Need advice about which tool to choose?Ask the StackShare community!

Jobs that mention Prometheus and StatsD as a desired skillset
San Francisco, United States
What companies use Prometheus?
What companies use StatsD?
See which teams inside your own company are using Prometheus or StatsD.
Sign up for StackShare EnterpriseLearn More

Sign up to get full access to all the companiesMake informed product decisions

What tools integrate with Prometheus?
What tools integrate with StatsD?

Sign up to get full access to all the tool integrationsMake informed product decisions

Blog Posts

Dec 8 2020 at 5:50PM


May 21 2020 at 12:02AM

Rancher Labs

KubernetesAmazon EC2Grafana+12
What are some alternatives to Prometheus and StatsD?
Datadog is the leading service for cloud-scale monitoring. It is used by IT, operations, and development teams who build and operate applications that run on dynamic or hybrid cloud infrastructure. Start monitoring in minutes with Datadog!
Grafana is a general purpose dashboard and graph composer. It's focused on providing rich ways to visualize time series metrics, mainly though graphs but supports other ways to visualize data through a pluggable panel architecture. It currently has rich support for for Graphite, InfluxDB and OpenTSDB. But supports other data sources via plugins.
New Relic
The world’s best software and DevOps teams rely on New Relic to move faster, make better decisions and create best-in-class digital experiences. If you run software, you need to run New Relic. More than 50% of the Fortune 100 do too.
InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
See all alternatives