Chronograf vs Prometheus

Overview

Prometheus

Stacks4.8K

Followers3.8K

Votes239

GitHub Stars61.1K

Forks9.9K

Chronograf

Stacks44

Followers57

Votes5

GitHub Stars30.8K

Forks3.7K

Chronograf vs Prometheus: What are the differences?

Data Collection: A key difference between Chronograf and Prometheus is in how they collect data. Prometheus follows a pull-based model where it scrapes metrics from instrumented jobs at configured intervals. On the other hand, Chronograf can work with various data sources like InfluxDB, but it does not have native support for scraping metrics like Prometheus.
Querying and Alerting: Another difference lies in querying capabilities and alerting mechanisms. Prometheus has a powerful querying language called PromQL, which allows users to perform complex queries on the collected data. It also has a built-in alerting system for creating and managing alerts based on defined conditions. In contrast, Chronograf has a more visual query builder tool for querying data and managing alerts in a graphical interface.
Integrations: When it comes to integrations, Prometheus has a vast ecosystem of exporters and integrations with various technologies and platforms, making it versatile and widely adopted. Chronograf, while compatible with InfluxDB and the TICK Stack, may require additional setup or connectors for integration with other systems, making it less flexible in terms of integrations.
Scalability: In terms of scalability, Prometheus is known for its horizontal scalability where multiple instances can be deployed to handle large workloads efficiently. Chronograf, being part of the TICK Stack, can benefit from InfluxDB's scalability features but may not be as scalable on its own as Prometheus.
Ecosystem Support: Prometheus has a strong community and ecosystem support with extensive documentation, community-contributed exporters, and third-party tools. Chronograf, while being a part of the InfluxData ecosystem, may have a comparatively smaller community and ecosystem support in comparison to Prometheus.
Data Persistence: Prometheus stores its data locally by default, which is suitable for short-term storage and analysis. In contrast, Chronograf typically works with InfluxDB as its data store, providing a robust solution for long-term data retention and scalability.

In Summary, Chronograf and Prometheus differ in data collection methods, querying capabilities, integrations, scalability, ecosystem support, and data persistence options.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs

CLI (Node.js)

Manual

Advice on Prometheus, Chronograf

Raja Subramaniam

Aug 27, 2019

Needs adviceon

Prometheus

Kubernetes

Sysdig

We have Prometheus as a monitoring engine as a part of our stack which contains Kubernetes cluster, container images and other open source tools. Also, I am aware that Sysdig can be integrated with Prometheus but I really wanted to know whether Sysdig or sysdig+prometheus will make better monitoring solution.

779k views779k

Comments

Susmita

Senior SRE at African Bank

Jul 28, 2020

Needs adviceon

Grafana

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.

869k views869k

Comments

Mat

Head of Cloud at Mats Cloud

Oct 30, 2019

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.

794k views794k

Comments

Detailed Comparison

Prometheus	Chronograf
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.	The complete interface. allows you to quickly see the data that you have stored, so you can build robust queries and alerts.
Dimensional data; Powerful queries; Great visualization; Efficient storage; Precise alerting; Simple operation	-
Statistics
GitHub Stars 61.1K	GitHub Stars 30.8K
GitHub Forks 9.9K	GitHub Forks 3.7K
Stacks 4.8K	Stacks 44
Followers 3.8K	Followers 57
Votes 239	Votes 5
Pros & Cons
Pros 47 Powerful easy to use monitoring 38 Flexible query language 32 Dimensional data model 27 Alerts 23 Active and responsive community Cons 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	Pros 1 It´s extremely compatible with Influxdb 1 Can build dashboards 1 Free 1 Open Source 1 Easy
Integrations
Grafana	No integrations available

What are some alternatives to Prometheus, Chronograf?

Grafana

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.

Kibana

Kibana is an open source (Apache Licensed), browser based analytics and search dashboard for Elasticsearch. Kibana is a snap to setup and start using. Kibana strives to be easy to get started with, while also being flexible and powerful, just like Elasticsearch.

Nagios

Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License.

Netdata

Netdata collects metrics per second & presents them in low-latency dashboards. It's designed to run on all of your physical & virtual servers, cloud deployments, Kubernetes clusters & edge/IoT devices, to monitor systems, containers & apps

Zabbix

Zabbix is a mature and effortless enterprise-class open source monitoring solution for network monitoring and application monitoring of millions of metrics.

Sensu

Sensu is the future-proof solution for multi-cloud monitoring at scale. The Sensu monitoring event pipeline empowers businesses to automate their monitoring workflows and gain deep visibility into their multi-cloud environments.

Graphite

Graphite does two things: 1) Store numeric time-series data and 2) Render graphs of this data on demand

Lumigo

Lumigo is an observability platform built for developers, unifying distributed tracing with payload data, log management, and real-time metrics to help you deeply understand and troubleshoot your systems.

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).

Jaeger

Jaeger, a Distributed Tracing System

Related Comparisons

Chronograf vs Prometheus: What are the differences?

Data Collection: A key difference between Chronograf and Prometheus is in how they collect data. Prometheus follows a pull-based model where it scrapes metrics from instrumented jobs at configured intervals. On the other hand, Chronograf can work with various data sources like InfluxDB, but it does not have native support for scraping metrics like Prometheus.
Querying and Alerting: Another difference lies in querying capabilities and alerting mechanisms. Prometheus has a powerful querying language called PromQL, which allows users to perform complex queries on the collected data. It also has a built-in alerting system for creating and managing alerts based on defined conditions. In contrast, Chronograf has a more visual query builder tool for querying data and managing alerts in a graphical interface.
Integrations: When it comes to integrations, Prometheus has a vast ecosystem of exporters and integrations with various technologies and platforms, making it versatile and widely adopted. Chronograf, while compatible with InfluxDB and the TICK Stack, may require additional setup or connectors for integration with other systems, making it less flexible in terms of integrations.
Scalability: In terms of scalability, Prometheus is known for its horizontal scalability where multiple instances can be deployed to handle large workloads efficiently. Chronograf, being part of the TICK Stack, can benefit from InfluxDB's scalability features but may not be as scalable on its own as Prometheus.
Ecosystem Support: Prometheus has a strong community and ecosystem support with extensive documentation, community-contributed exporters, and third-party tools. Chronograf, while being a part of the InfluxData ecosystem, may have a comparatively smaller community and ecosystem support in comparison to Prometheus.
Data Persistence: Prometheus stores its data locally by default, which is suitable for short-term storage and analysis. In contrast, Chronograf typically works with InfluxDB as its data store, providing a robust solution for long-term data retention and scalability.

In Summary, Chronograf and Prometheus differ in data collection methods, querying capabilities, integrations, scalability, ecosystem support, and data persistence options.

Chronograf vs Prometheus

Overview