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Kibana vs Redash: What are the differences?
Introduction
Kibana and Redash are both data visualization and exploration tools, but they have some key differences that set them apart.
1. Data Sources:
Kibana is primarily designed to work with Elasticsearch, a distributed, RESTful search and analytics engine, while Redash can connect to various data sources such as SQL databases, MongoDB, Google Sheets, and more. This means that Kibana is more focused on analyzing and visualizing data stored in Elasticsearch, whereas Redash offers greater flexibility in working with different data sources.
2. Ease of Use:
Kibana provides a more user-friendly interface that is intuitive and easy to navigate, making it suitable for both technical and non-technical users. On the other hand, Redash offers a simpler interface with fewer features, which can make it easier for beginners to get started, but may limit the capabilities for more advanced users.
3. Visualization Options:
Both Kibana and Redash offer a range of visualization options, including charts, graphs, and dashboards. However, Kibana provides a wider variety of visualizations and customization options, allowing users to create more complex and interactive visual representations of their data. Redash, while still offering basic visualizations, may be more limited in terms of advanced visualization options.
4. Alerting and Monitoring:
Kibana includes built-in alerting and monitoring functionality, allowing users to set up alerts based on predefined conditions and monitor the health and performance of their data. Redash, on the other hand, does not have built-in alerting and monitoring features, although it can be integrated with external tools for this purpose.
5. Collaboration and Sharing:
Both Kibana and Redash offer features for collaboration and sharing of visualizations and dashboards. However, Kibana provides more advanced collaboration options, allowing users to work together on dashboards in real-time and share visualizations with others through its user management system. Redash also supports collaboration and sharing, but it may require additional setup and configuration.
6. Community Support:
Kibana has a larger and more active community support compared to Redash. This means that there are more resources, tutorials, and plugins available for Kibana, which can be helpful in troubleshooting and extending its functionalities. Redash also has a community support, but it may be relatively smaller compared to Kibana.
In summary, Kibana is more focused on Elasticsearch and provides a wider range of visualization options, built-in alerting and monitoring features, advanced collaboration options, and has a larger community support. Redash, on the other hand, offers flexibility in working with various data sources, a simpler interface, basic visualizations, and collaboration and sharing capabilities, but with a potentially smaller community support.
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 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 Redash
- Open Source9
- SQL Friendly3
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Cons of Kibana
- Unintuituve6
- Elasticsearch is huge4
- Hardweight UI3
- Works on top of elastic only3
Cons of Redash
- All results are loaded into RAM before displaying1
- Memory Leaks1
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