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Datadog vs Zipkin: What are the differences?
Introduction
In this comparison, we will highlight the key differences between Datadog and Zipkin, two popular distributed tracing systems used for monitoring and troubleshooting applications.
Architecture: Datadog is a SaaS-based monitoring platform that offers a wide range of monitoring capabilities beyond just distributed tracing, including infrastructure monitoring and logs analysis. On the other hand, Zipkin is an open-source distributed tracing system that focuses solely on tracing application requests as they travel through multiple microservices.
Ease of Use: Datadog provides a user-friendly interface and offers various integrations and agents for easy implementation into different environments. It also offers out-of-the-box dashboards and alerts for quick setup. In contrast, Zipkin requires more manual configuration and might require additional plugins or tools to integrate and visualize the tracing data.
Scalability: Datadog can handle large-scale applications and supports high ingestion rates of tracing data. It also provides automatic scaling and load balancing capabilities. Zipkin, being an open-source system, may require more effort in setting up a scalable environment, especially in scenarios with heavy trace data traffic.
Supported Languages/Frameworks: Datadog has extensive language and framework support, providing libraries and instrumentation for various programming languages and frameworks, making it easy to trace applications across different technology stacks. Zipkin also has support for many languages but might require additional community-provided instrumentation for less common frameworks.
Integrations and Ecosystem: Datadog integrates with a wide range of other tools and platforms, allowing a comprehensive monitoring and observability stack. It has built-in integrations for cloud platforms, databases, messaging systems, and more. Zipkin, being open-source, has a growing ecosystem of plugins and integrations, but it may require more effort to integrate with specific platforms or tools.
Pricing and Commercial Support: Datadog offers a paid SaaS solution with different pricing tiers based on usage. It also provides commercial support and has a dedicated customer success team. Zipkin, being open-source, is free to use but may lack official commercial support. Organizations using Zipkin might need to rely on community support or internal resources for troubleshooting or customization.
In Summary, Datadog and Zipkin offer different approaches to distributed tracing. Datadog is a comprehensive monitoring platform with distributed tracing as one of its features, while Zipkin is a dedicated open-source distributed tracing system. Datadog provides ease of use, extensive integrations, and commercial support, whereas Zipkin offers flexibility, scalability, and a strong open-source community. Choose based on your specific needs and requirements.
Hey there! We are looking at Datadog, Dynatrace, AppDynamics, and New Relic as options for our web application monitoring.
Current Environment: .NET Core Web app hosted on Microsoft IIS
Future Environment: Web app will be hosted on Microsoft Azure
Tech Stacks: IIS, RabbitMQ, Redis, Microsoft SQL Server
Requirement: Infra Monitoring, APM, Real - User Monitoring (User activity monitoring i.e., time spent on a page, most active page, etc.), Service Tracing, Root Cause Analysis, and Centralized Log Management.
Please advise on the above. Thanks!
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 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 Datadog
- Monitoring for many apps (databases, web servers, etc)140
- Easy setup107
- Powerful ui87
- Powerful integrations84
- Great value70
- Great visualization54
- Events + metrics = clarity46
- Notifications41
- Custom metrics41
- Flexibility39
- Free & paid plans19
- Great customer support16
- Makes my life easier15
- Adapts automatically as i scale up10
- Easy setup and plugins9
- Super easy and powerful8
- In-context collaboration7
- AWS support7
- Rich in features6
- Docker support5
- Cute logo4
- Simple, powerful, great for infra4
- Monitor almost everything4
- Full visibility of applications4
- Easy to Analyze4
- Cost4
- Source control and bug tracking4
- Best than others4
- Automation tools4
- Best in the field3
- Expensive3
- Good for Startups3
- Free setup3
- APM2
Pros of Zipkin
- Open Source10
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Cons of Datadog
- Expensive20
- No errors exception tracking4
- External Network Goes Down You Wont Be Logging2
- Complicated1
Cons of Zipkin
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