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Grafana vs Kapacitor: What are the differences?
Introduction
Grafana and Kapacitor are both popular tools in the field of data monitoring and analysis. Grafana is a data visualization and monitoring tool, while Kapacitor is a data processing engine. Although they have some similarities in terms of their purpose, there are key differences that set them apart.
Architecture: Grafana is a lightweight, web-based tool that connects to various data sources and displays information in customizable dashboards. It primarily focuses on data visualization and exploration. On the other hand, Kapacitor is a part of the TICK stack (Telegraf, InfluxDB, Chronograf, and Kapacitor) and is designed for real-time stream processing and alerting. It allows users to define and apply complex data analysis tasks in a scalable manner.
Functionality: Grafana primarily focuses on visualizing data from different sources, allowing users to build and customize dashboards using a drag-and-drop interface. It supports a wide range of data sources and offers a variety of visualizations, including graphs, tables, and heatmaps. In contrast, Kapacitor provides a set of tools for creating and running data processing tasks. It allows users to define complex data analysis workflows, apply mathematical functions, filter and aggregate data, and trigger alerts based on predefined conditions.
Data sources: Grafana supports a wide range of data sources, including databases, time-series databases, cloud services, and APIs. It integrates with popular databases like MySQL, PostgreSQL, and Prometheus, as well as cloud services like Amazon Web Services and Google Cloud Platform. Kapacitor, on the other hand, is tightly integrated with InfluxDB, a high-performance time-series database. It directly processes the data stored in InfluxDB and provides real-time data analysis and alerting capabilities.
Alerting: While Grafana offers basic alerting capabilities, it relies on external notification services like email or messaging apps to send alerts. Alerts can be triggered based on predefined conditions, such as a threshold being exceeded or a pattern being detected. Kapacitor, on the other hand, is designed specifically for real-time alerting and provides a more powerful and flexible alerting system. It allows users to define complex alerting rules using a domain-specific language and provides built-in integrations with various notification services.
Scalability: Grafana is designed to be lightweight and efficient, making it suitable for small-scale deployments. However, it may face scalability challenges when dealing with a large amount of data or high query loads. Kapacitor, on the other hand, is built to handle large-scale data processing and is designed to be scalable and reliable. It can process high-frequency data streams and distribute the workload across multiple instances for improved performance.
Community and ecosystem: Grafana has a large and active community, with a wide range of plugins and extensions available. It has become a popular choice for data visualization and monitoring in various industries. Kapacitor, on the other hand, is more specialized and has a smaller community compared to Grafana. However, it benefits from being a part of the InfluxData ecosystem and integrates well with other tools in the TICK stack.
In Summary, Grafana is a lightweight data visualization and monitoring tool with a focus on customizable dashboards, while Kapacitor is a real-time data processing engine with advanced alerting capabilities. Grafana supports a wide range of data sources and is suitable for small-scale deployments, while Kapacitor is tightly integrated with InfluxDB and is designed for large-scale data processing and alerting.
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.
You can look out for Prometheus Instrumentation (https://prometheus.io/docs/practices/instrumentation/) Client Library available in various languages https://prometheus.io/docs/instrumenting/clientlibs/ to create the custom metric you need for AS4000 and then Grafana can query the newly instrumented metric to show on the dashboard.
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.
this is quite affordable and provides what you seem to be looking for. you can see a whole thing about the APM space here https://www.apmexperts.com/observability/ranking-the-observability-offerings/
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.
From a StackShare Community member: “We need better analytics & insights into our Elasticsearch cluster. Grafana, which ships with advanced support for Elasticsearch, looks great but isn’t officially supported/endorsed by Elastic. Kibana, on the other hand, is made and supported by Elastic. I’m wondering what people suggest in this situation."
For our Predictive Analytics platform, we have used both Grafana and Kibana
- Grafana based demo video: https://www.youtube.com/watch?v=tdTB2AcU4Sg
- Kibana based reporting screenshot: https://imgur.com/vuVvZKN
Kibana has predictions and ML algorithms support, so if you need them, you may be better off with Kibana . The multi-variate analysis features it provide are very unique (not available in Grafana).
For everything else, definitely Grafana . Especially the number of supported data sources, and plugins clearly makes Grafana a winner (in just visualization and reporting sense). Creating your own plugin is also very easy. The top pros of Grafana (which it does better than Kibana ) are:
- Creating and organizing visualization panels
- Templating the panels on dashboards for repetetive tasks
- Realtime monitoring, filtering of charts based on conditions and variables
- Export / Import in JSON format (that allows you to version and save your dashboard as part of git)
I use both Kibana and Grafana on my workplace: Kibana for logging and Grafana for monitoring. Since you already work with Elasticsearch, I think Kibana is the safest choice in terms of ease of use and variety of messages it can manage, while Grafana has still (in my opinion) a strong link to metrics
After looking for a way to monitor or at least get a better overview of our infrastructure, we found out that Grafana (which I previously only used in ELK stacks) has a plugin available to fully integrate with Amazon CloudWatch . Which makes it way better for our use-case than the offer of the different competitors (most of them are even paid). There is also a CloudFlare plugin available, the platform we use to serve our DNS requests. Although we are a big fan of https://smashing.github.io/ (previously dashing), for now we are starting with Grafana .
I use Kibana because it ships with the ELK stack. I don't find it as powerful as Splunk however it is light years above grepping through log files. We previously used Grafana but found it to be annoying to maintain a separate tool outside of the ELK stack. We were able to get everything we needed from Kibana.
Kibana should be sufficient in this architecture for decent analytics, if stronger metrics is needed then combine with Grafana. Datadog also offers nice overview but there's no need for it in this case unless you need more monitoring and alerting (and more technicalities).
@Kibana, of course, because @Grafana looks like amateur sort of solution, crammed with query builder grouping aggregates, but in essence, as recommended by CERN - KIbana is the corporate (startup vectored) decision.
Furthermore, @Kibana comes with complexity adhering ELK stack, whereas @InfluxDB + @Grafana & co. recently have become sophisticated development conglomerate instead of advancing towards a understandable installation step by step inheritance.
Pros of Grafana
- Beautiful89
- Graphs are interactive68
- Free57
- Easy56
- Nicer than the Graphite web interface34
- Many integrations26
- Can build dashboards18
- Easy to specify time window10
- Can collaborate on dashboards10
- Dashboards contain number tiles9
- Open Source5
- Integration with InfluxDB5
- Click and drag to zoom in5
- Authentification and users management4
- Threshold limits in graphs4
- Alerts3
- It is open to cloud watch and many database3
- Simple and native support to Prometheus3
- Great community support2
- You can use this for development to check memcache2
- You can visualize real time data to put alerts2
- Grapsh as code0
- Plugin visualizationa0
Pros of Kapacitor
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Cons of Grafana
- No interactive query builder1
Cons of Kapacitor
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