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Grafana vs Tableau: What are the differences?
Introduction
In this article, we will explore the key differences between Grafana and Tableau. Both Grafana and Tableau are widely used data visualization tools, but they have distinct features and functionalities that set them apart from each other.
Data Source Connectivity: Grafana primarily focuses on monitoring and observability and provides support for a wide range of data sources, including databases, time series data, cloud storage, and APIs. On the other hand, Tableau offers connectivity to various data sources as well, but it is more focused on traditional business intelligence and analytics, offering robust integration with commonly used data sources such as databases, spreadsheets, and cloud platforms.
Ease of Use and Learning Curve: Grafana is known for its user-friendly interface and ease of use, allowing users to quickly create and customize dashboards with its intuitive drag-and-drop functionality. It also offers a simple query language called Grafana Query Language (GQL) for data manipulation. Tableau, on the other hand, provides a more feature-rich interface with a steeper learning curve. It offers a wide range of features and capabilities, making it suitable for complex data analysis and advanced data visualization.
Visualization Options: Grafana provides a rich set of visualization options, primarily focused on time series data with features such as graphs, gauges, and heat maps. It also allows users to create alerts and notifications based on data thresholds. Tableau, on the other hand, offers a diverse range of visualizations including charts, maps, scatter plots, and more. It also provides advanced analytics features such as forecasting, clustering, and trend analysis.
Community and Ecosystem: Grafana has a strong open-source community and a wide ecosystem of plugins and extensions, allowing users to extend its capabilities and integrate with various data sources and services. Tableau also has a thriving community but is more focused on its commercial offering, with a dedicated marketplace for pre-built dashboards, data connectors, and extensions.
Cost and Licensing: Grafana is open-source software available under the Apache License 2.0, which means it is free to use and modify. However, additional costs may arise if using premium data sources or enterprise-level support. Tableau, on the other hand, is a commercial product with different licensing options, including a desktop version for individual users and enterprise-level subscriptions that provide additional features and support. This makes Tableau more costly, especially for organizations requiring a large number of licenses.
Customization and SDKs: Grafana offers extensive customization options through its plugins and a rich set of APIs, allowing users to modify and extend its functionality. It also offers software development kits (SDKs) for building custom data sources and visualizations. Tableau also provides customization options through its JavaScript API but has more limited extensibility compared to Grafana.
In summary, Grafana is well-suited for real-time monitoring and observability use cases with its wide range of data source compatibility and user-friendly interface, while Tableau is more focused on traditional business intelligence and analytics, offering advanced analytics capabilities, a variety of visualization options, and a larger ecosystem of pre-built dashboards and connectors. The choice between the two depends on the specific needs and requirements of the organization or individual users.
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.
Very easy-to-use UI. Good way to make data available inside the company for analysis.
Has some built-in visualizations and can be easily integrated with other JS visualization libraries such as D3.
Can be embedded into product to provide reporting functions.
Support team are helpful.
The only complain I have is lack of API support. Hard to track changes as codes and automate report deployment.
Power BI is really easy to start with. If you have just several Excel sheets or CSV files, or you build your first automated pipeline, it is actually quite intuitive to build your first reports.
And as we have kept growing, all the additional features and tools were just there within the Azure platform and/or Office 365.
Since we started building Mews, we have already passed several milestones in becoming start up, later also a scale up company and now getting ready to grow even further, and during all these phases Power BI was just the right tool for us.
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 Tableau
- Capable of visualising billions of rows6
- Intuitive and easy to learn1
- Responsive1
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Cons of Grafana
- No interactive query builder1
Cons of Tableau
- Very expensive for small companies3