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Kibana vs New Relic: What are the differences?
Kibana is an open-source data visualization tool, while New Relic is a SaaS-based application performance monitoring platform. Let's explore the key differences between them.
Integration with Elasticsearch: Kibana is tightly integrated with Elasticsearch, allowing users to easily visualize and analyze data stored in Elasticsearch. On the other hand, New Relic is primarily focused on monitoring and performance management, and while it does provide some integration capabilities, it is not as extensive as Kibana's.
Scope of Monitoring: Kibana is more suited for analyzing log and time-series data, providing detailed insights into system and application performance. It allows users to create various visualizations like dashboards, maps, and charts. In contrast, New Relic offers a broader scope of monitoring, covering application performance, user experience, infrastructure, and cloud services.
Pricing Model: Kibana is open-source and free to use, making it more cost-effective for organizations. However, it does require expertise in Elasticsearch and the maintenance of server infrastructure. New Relic, on the other hand, offers different pricing tiers based on the depth of monitoring required, making it suitable for organizations that require more comprehensive monitoring capabilities but at a higher cost.
Alerting and Notification: Kibana primarily relies on Elasticsearch Watcher for alerting and notification capabilities. It allows users to set up alerts based on predefined conditions and send notifications through various channels. New Relic, on the other hand, has a built-in alerting mechanism that is tightly integrated with its monitoring capabilities, providing more advanced alerting and notification features out-of-the-box.
Deployment and Scalability: Kibana can be deployed on-premises or in the cloud, depending on the organization's preference and requirements. It provides scalability through Elasticsearch's distributed architecture. New Relic, however, is a cloud-based solution, offering easy deployment and scalability without the need for managing infrastructure.
Support and Documentation: Kibana has a large and active open-source community, providing extensive documentation, tutorials, and support forums. This allows users to find resources and solutions easily. New Relic provides dedicated customer support and has a comprehensive knowledge base, offering assistance to users in a more personalized manner.
In summary, Kibana is an open-source, tightly integrated solution with Elasticsearch, providing extensive monitoring and visualization capabilities. It is well-suited for log and time-series data analysis. New Relic, on the other hand, offers a broader scope of monitoring, integrated alerting mechanisms, and simplified deployment and scalability as a cloud-based solution.
We are looking for a centralised monitoring solution for our application deployed on Amazon EKS. We would like to monitor using metrics from Kubernetes, AWS services (NeptuneDB, AWS Elastic Load Balancing (ELB), Amazon EBS, Amazon S3, etc) and application microservice's custom metrics.
We are expected to use around 80 microservices (not replicas). I think a total of 200-250 microservices will be there in the system with 10-12 slave nodes.
We tried Prometheus but it looks like maintenance is a big issue. We need to manage scaling, maintaining the storage, and dealing with multiple exporters and Grafana. I felt this itself needs few dedicated resources (at least 2-3 people) to manage. Not sure if I am thinking in the correct direction. Please confirm.
You mentioned Datadog and Sysdig charges per host. Does it charge per slave node?
Can't say anything to Sysdig. I clearly prefer Datadog as
- they provide plenty of easy to "switch-on" plugins for various technologies (incl. most of AWS)
- easy to code (python) agent plugins / api for own metrics
- brillant dashboarding / alarms with many customization options
- pricing is OK, there are cheaper options for specific use cases but if you want superior dashboarding / alarms I haven't seen a good competitor (despite your own Prometheus / Grafana / Kibana dog food)
IMHO NewRelic is "promising since years" ;) good ideas but bad integration between their products. Their Dashboard query language is really nice but lacks critical functions like multiple data sets or advanced calculations. Needless to say you get all of that with Datadog.
Need help setting up a monitoring / logging / alarm infrastructure? Send me a message!
Hi Medeti,
you are right. Building based on your stack something with open source is heavy lifting. A lot of people I know start with such a set-up, but quickly run into frustration as they need to dedicated their best people to build a monitoring which is doing the job in a professional way.
As you are microservice focussed and are looking for 'low implementation and maintenance effort', you might want to have a look at INSTANA, which was built with modern tool stacks in mind. https://www.instana.com/apm-for-microservices/
We have a public sand-box available if you just want to have a look at the product once and of course also a free-trial: https://www.instana.com/getting-started-with-apm/
Let me know if you need anything on top.
I have hands on production experience both with New Relic and Datadog. I personally prefer Datadog over NewRelic because of the UI, the Documentation and the overall user/developer experience.
NewRelic however, can do basically the same things as Datadog can, and some of the features like alerting have been present in NewRelic for longer than in Datadog. The cool thing about NewRelic is their last-summer-updated pricing: you no longer pay per host but after data you send towards New Relic. This can be a huge cost saver depending on your particular setup
I'd go for Datadog, but given you have lots of containers I would also make a cost calculation. If the price difference is significant and there's a budget constraint NewRelic might be the better choice.
I need to choose a monitoring tool for my project, but currently, my application doesn't have much load or many users. My application is not generating GBs of data. We don't want to send the user information to New Relic because it's a 3rd party tool. And we can deploy Kibana locally on our server. What should I use, Kibana or New Relic?
Kibana and ELK stack is way far better in enterprise solution. But if you are going to deploy something smal, it does't worth the configuration and maintenance of the ELK stack. You'll have lots of challenges every day. If you have a small team, I do not recommend on-promiss ELK. You can also consider ELK hosted services which are very easier to use, like logz.io
New Relic's value to me is the ability to see how end users perceive the application. Kibana is going to be limited to what is sent to it. The value to larger companies is paying New Relic to package up knowledge on what are typical trigger values. If you your scope is small, not a global website for example, and your key outage risks are local events then Kibana would be a low cost solution but you may be the sole provider of configuration logic.
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.
I haven't heard much about Datadog until about a year ago. Ironically, the NewRelic sales person who I had a series of trainings with was trash talking about Datadog a lot. That drew my attention to Datadog and I gave it a try at another client project where we needed log handling, dashboards and alerting.
In 2019, Datadog was already offering log management and from that perspective, it was ahead of NewRelic. Other than that, from my perspective, the two tools are offering a very-very similar set of tools. Therefore I wouldn't say there's a significant difference between the two, the decision is likely a matter of taste. The pricing is also very similar.
The reasons why we chose Datadog over NewRelic were:
- The presence of log handling feature (since then, logging is GA at NewRelic as well since falls 2019).
- The setup was easier even though I already had experience with NewRelic, including participation in NewRelic trainings.
- The UI of Datadog is more compact and my experience is smoother.
- The NewRelic UI is very fragmented and New Relic One is just increasing this experience for me.
- The log feature of Datadog is very well designed, I find very useful the tagging logs with services. The log filtering is also very awesome.
Bottom line is that both tools are great and it makes sense to discover both and making the decision based on your use case. In our case, Datadog was the clear winner due to its UI, ease of setup and the awesome logging and alerting features.
I chose Datadog APM because the much better APM insights it provides (flamegraph, percentiles by default).
The drawbacks of this decision are we had to move our production monitoring to TimescaleDB + Telegraf instead of NR Insight
NewRelic is definitely easier when starting out. Agent is only a lib and doesn't require a daemon
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 New Relic
- Easy setup415
- Really powerful344
- Awesome visualization245
- Ease of use194
- Great ui151
- Free tier106
- Great tool for insights80
- Heroku Integration66
- Market leader55
- Peace of mind49
- Push notifications21
- Email notifications20
- Heroku Add-on17
- Error Detection and Alerting16
- Multiple language support13
- SQL Analysis11
- Server Resources Monitoring11
- Transaction Tracing9
- Apdex Scores8
- Azure Add-on8
- Analysis of CPU, Disk, Memory, and Network7
- Detailed reports7
- Performance of External Services6
- Error Analysis6
- Application Availability Monitoring and Alerting6
- Application Response Times6
- Most Time Consuming Transactions5
- JVM Performance Analyzer (Java)5
- Browser Transaction Tracing4
- Top Database Operations4
- Easy to use4
- Application Map3
- Weekly Performance Email3
- Pagoda Box integration3
- Custom Dashboards3
- Easy to setup2
- Background Jobs Transaction Analysis2
- App Speed Index2
- Super Expensive1
- Team Collaboration Tools1
- Metric Data Retention1
- Metric Data Resolution1
- Worst Transactions by User Dissatisfaction1
- Real User Monitoring Overview1
- Real User Monitoring Analysis and Breakdown1
- Time Comparisons1
- Access to Performance Data API1
- Incident Detection and Alerting1
- Best of the best, what more can you ask for1
- Best monitoring on the market1
- Rails integration1
- Free1
- Proce0
- Price0
- Exceptions0
- Cost0
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Cons of Kibana
- Unintuituve7
- Works on top of elastic only4
- Elasticsearch is huge4
- Hardweight UI3
Cons of New Relic
- Pricing model doesn't suit microservices20
- UI isn't great10
- Expensive7
- Visualizations aren't very helpful7
- Hard to understand why things in your app are breaking5