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Datadog vs Instana: What are the differences?
Introduction:
Datadog and Instana are both APM (Application Performance Monitoring) tools that provide monitoring and observability solutions for cloud-native applications. While they have similar purposes, there are key differences between them that make each tool unique. In this article, we will explore these differences and help you understand which tool might be a better fit for your specific needs.
Deployment and Implementation: Datadog offers an agent-based deployment model where an agent needs to be installed on the servers or containers to collect and send data to Datadog. On the other hand, Instana uses an agentless approach that leverages lightweight and automatic instrumentation to collect monitoring data. This key difference affects the ease of implementation and resource utilization for each tool.
Automated Application Mapping: Instana excels in automated application mapping, wherein it can automatically discover and monitor all components and dependencies of a dynamically changing application environment. Datadog also provides application mapping, but it relies on manual configuration and tagging to achieve similar functionality. This difference in automation can significantly impact the initial setup and ongoing maintenance of the monitoring infrastructure.
Distributed Tracing Capabilities: Datadog offers distributed tracing functionality, allowing you to trace a request's path through a distributed system, identify bottlenecks, and analyze performance issues. Instana, on the other hand, goes a step further by automatically generating and visualizing distributed traces without any manual configuration. This difference makes Instana the go-to choice for teams heavily reliant on microservices architecture.
Root Cause Analysis: Instana provides automatic root cause analysis (RCA) capabilities, where it leverages artificial intelligence and machine learning algorithms to detect anomalies and identify the root cause of performance issues. While Datadog also offers RCA features, they are more manual and require users to define and configure alert thresholds to trigger RCA. Instana's AI-driven RCA speeds up troubleshooting and helps address issues proactively.
Real-Time Application Monitoring: Instana excels in real-time monitoring, providing extremely low-latency and high-resolution data collection. It captures every change, transaction, and metric in real-time, allowing you to identify and address issues as they occur. Datadog, although capable of real-time monitoring, may have slightly higher latencies during data collection and retention, which can impact the accuracy of monitoring alerts and analysis for ultra-critical systems.
Integration Ecosystem: Datadog boasts an extensive integration ecosystem, with support for numerous third-party tools and services, making it a versatile choice for organizations with complex monitoring environments. Instana offers integrations as well, but the ecosystem is relatively smaller compared to Datadog. If your organization heavily relies on specific integrations, it's essential to analyze if the required integrations are available for seamless workflows.
In Summary, while both Datadog and Instana are APM tools, their differences lie in deployment models, automated application mapping, distributed tracing capabilities, root cause analysis, real-time monitoring, and integration ecosystems. Choosing between them depends on specific needs such as ease of implementation, automation, traceability requirements, application complexity, troubleshooting preferences, and the availability of required integrations.
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)139
- 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
- AWS support7
- In-context collaboration7
- Rich in features6
- Docker support5
- Cost4
- Full visibility of applications4
- Monitor almost everything4
- Cute logo4
- Automation tools4
- Source control and bug tracking4
- Simple, powerful, great for infra4
- Easy to Analyze4
- Best than others4
- Best in the field3
- Expensive3
- Good for Startups3
- Free setup3
- APM2
Pros of Instana
- Flexible pricing4
- Easy to integrate4
- Insight into RCA3
- Self service3
- Simple query interface2
- Automatic1
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Cons of Datadog
- Expensive20
- No errors exception tracking4
- External Network Goes Down You Wont Be Logging2
- Complicated1