Need advice about which tool to choose?Ask the StackShare community!
Datadog vs JavaMelody: What are the differences?
Introduction
Datadog and JavaMelody are two popular monitoring tools used for performance monitoring and application tracking. Both tools have their own unique features and capabilities that make them suitable for different use cases. In this article, we will discuss the key differences between Datadog and JavaMelody.
Data Collection: One major difference between Datadog and JavaMelody is the way they collect data. Datadog uses an agent-based approach to collect data from various sources, including servers, applications, and infrastructure. It provides a wide range of integrations and plugins to collect and analyze data. On the other hand, JavaMelody is a Java monitoring tool that collects data directly from Java applications without requiring any agent installation. It provides detailed metrics and performance data specific to Java applications.
Scalability and Flexibility: Datadog is designed to handle large-scale monitoring and provides scalability and flexibility for monitoring various environments and applications. It supports distributed systems, cloud platforms, microservices, and containerized applications. It offers advanced features like automatic scaling, anomaly detection, and predictive analytics. JavaMelody, on the other hand, is primarily focused on monitoring Java applications and provides detailed insights into JVM metrics, servlets, SQL queries, threads, and server statistics. It is a lightweight and flexible tool that can be easily integrated into Java applications.
Alerting and Notification: Datadog offers robust alerting and notification capabilities. It allows users to set up custom alerts based on predefined thresholds and conditions. It supports various notification channels like email, SMS, Slack, PagerDuty, etc. It also provides intelligent alerting features like anomaly detection and machine learning algorithms. JavaMelody, on the other hand, does not have built-in alerting and notification capabilities. Users need to implement custom logic or integrate with other monitoring tools to set up alerts.
Infrastructure Monitoring: Datadog provides comprehensive infrastructure monitoring capabilities. It collects metrics and data from servers, networks, cloud platforms, containers, and other infrastructure components. It offers real-time monitoring, visualization, and troubleshooting tools for infrastructure monitoring. JavaMelody, on the other hand, mainly focuses on application monitoring and does not provide extensive infrastructure monitoring features.
Integration and Ecosystem: Datadog offers a wide range of integrations and supports various technologies, frameworks, and platforms. It provides plugins, APIs, and SDKs for easy integration with different systems and applications. It has a rich ecosystem with a marketplace for additional integrations and extensions. JavaMelody, on the other hand, is primarily focused on Java applications and does not provide extensive integration capabilities.
Ease of Use and User Interface: Datadog provides a user-friendly and intuitive interface for monitoring, analyzing, and visualizing data. It offers prebuilt dashboards, reports, and widgets for easy data visualization. It also provides collaboration and sharing features for teams. JavaMelody, on the other hand, has a simple and lightweight user interface. It provides detailed metrics and data in a tabular format, but it may require some technical expertise to interpret and analyze the data.
In summary, Datadog is a comprehensive monitoring tool that offers scalability, flexibility, and a wide range of features for infrastructure and application monitoring. JavaMelody, on the other hand, is a lightweight and focused Java monitoring tool that provides detailed insights into Java application performance. The choice between these tools depends on the specific monitoring needs and requirements of the application or environment.
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)137
- Easy setup107
- Powerful ui87
- Powerful integrations83
- Great value70
- Great visualization54
- Events + metrics = clarity46
- Custom metrics41
- Notifications41
- 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
- Source control and bug tracking4
- Automation tools4
- Cute logo4
- Monitor almost everything4
- Full visibility of applications4
- Simple, powerful, great for infra4
- Easy to Analyze4
- Best than others4
- Expensive3
- Best in the field3
- Free setup3
- Good for Startups3
- APM2
Pros of JavaMelody
- Easy to setup1
- Open source1
Sign up to add or upvote prosMake informed product decisions
Cons of Datadog
- Expensive19
- No errors exception tracking4
- External Network Goes Down You Wont Be Logging2
- Complicated1