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Grafana vs Kibana vs Splunk Cloud: What are the differences?
Introduction
This Markdown code provides a comparison between Grafana, Kibana, and Splunk Cloud, highlighting the key differences between these popular tools used for data visualization and analytics.
Grafana: Grafana is an open-source data visualization and monitoring tool that allows users to create and display dynamic dashboards. It supports multiple data sources and is widely used for real-time analytics and monitoring. One key difference is that Grafana focuses primarily on visualizing time-series data and is highly customizable, offering a wide range of plugins and integrations.
Kibana: Kibana is another open-source data visualization tool, primarily used for analyzing and exploring data stored in Elasticsearch. It provides powerful search capabilities, visualizations, and dashboards for the Elasticsearch data. Unlike Grafana, Kibana is tightly integrated with Elasticsearch and is commonly used as the front-end tool for Elasticsearch clusters.
Splunk Cloud: Splunk Cloud is a cloud-based data analytics platform that enables organizations to collect, analyze, and visualize machine-generated data. It offers powerful search and reporting capabilities, allowing users to gain insights from large volumes of data. One key difference with Splunk Cloud is that it is a fully managed service provided by Splunk, eliminating the need for infrastructure management.
Data Sources: Grafana supports a wide range of data sources, including databases (e.g., MySQL, PostgreSQL), time-series databases (e.g., InfluxDB, Prometheus), and cloud platforms (e.g., AWS CloudWatch, Azure Monitor). Kibana, on the other hand, is primarily designed for data stored in Elasticsearch, with limited support for other data sources. Splunk Cloud can ingest data from various sources, including logs, metrics, events, and more, making it versatile in handling diverse data types.
Licensing Model: Grafana is an open-source tool released under the Apache License 2.0. It is free to use and has an active community contributing to its development. Kibana, being part of the Elastic Stack, follows Elastic's dual licensing model where the basic features are free and open-source, but additional modules and enterprise features require a subscription. Splunk Cloud follows a subscription-based licensing model, with pricing based on data ingestion volume.
Scalability and Deployment: Grafana can be deployed on-premises or in the cloud and offers high scalability, suitable for small to large-scale deployments. Kibana is typically deployed alongside Elasticsearch, providing horizontal scalability by adding more nodes to the Elasticsearch cluster. Splunk Cloud, being a managed service, offers automatic scalability based on data volumes and provides elastic resource allocation.
In summary, Grafana is a highly customizable data visualization tool with extensive plugin support, Kibana is tightly integrated with Elasticsearch and offers powerful search capabilities, while Splunk Cloud is a cloud-based, fully managed data analytics platform with versatile data ingestion capabilities.
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.
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.
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/
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 Kibana
- Easy to setup88
- Free65
- Can search text45
- Has pie chart21
- X-axis is not restricted to timestamp13
- Easy queries and is a good way to view logs9
- Supports Plugins6
- Dev Tools4
- More "user-friendly"3
- Can build dashboards3
- Out-of-Box Dashboards/Analytics for Metrics/Heartbeat2
- Easy to drill-down2
- Up and running1
Pros of Splunk Cloud
- More powerful & Integrates with on-prem & off-prem7
- Free3
- Powerful log analytics3
- Pci compliance1
- Production debugger1
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Cons of Grafana
- No interactive query builder1
Cons of Kibana
- Unintuituve7
- Works on top of elastic only4
- Elasticsearch is huge4
- Hardweight UI3