Datadog vs Sentry

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Datadog vs Sentry: What are the differences?

Datadog and Sentry are both monitoring tools used by developers and operations teams to track and analyze application performance. Here are the key differences between the two:

  1. Data collection and monitoring: Datadog focuses on collecting and analyzing metrics and logs from various sources, providing real-time monitoring and alerts. It offers comprehensive visibility into the infrastructure, application performance, and user experience. In contrast, Sentry is primarily an error and exception tracking tool. It focuses on capturing and reporting software errors and exceptions, helping developers identify and fix issues quickly.

  2. Alerting and troubleshooting: Datadog's alerting capabilities are highly customizable, allowing users to set up thresholds and conditions for generating alerts based on various metrics and logs. It also provides correlated data views to aid troubleshooting. Sentry, on the other hand, offers rich context for error reports, including stack traces, user data, and tags. This makes it easier for developers to identify and reproduce errors, leading to faster resolution.

  3. Deployment and integration: Datadog supports a wide range of integrations, making it compatible with different programming languages, frameworks, and devops tools. It provides libraries and agents for easy deployment across various environments. Sentry also offers integrations with popular development tools and frameworks, but its focus is primarily on capturing errors and exceptions in code. It provides SDKs and plugins for easy integration into different programming languages.

  4. User interface and visualization: Datadog offers a comprehensive and customizable user interface with interactive dashboards and visualizations. It allows users to create custom metrics, alerts, and monitors, and provides drag-and-drop functionality for easy visualization. Sentry, on the other hand, has a simpler user interface focused on error tracking and exception handling. Its interface provides detailed error reports with stack traces and other relevant information, aiding in debugging and fixing issues.

  5. Scalability and pricing: Datadog is designed for large-scale deployments and can handle monitoring needs for complex infrastructures. It offers various pricing plans with different feature sets based on the scale and requirements of the organization. Sentry, on the other hand, is more focused on capturing software errors and exceptions and may not scale to the same extent as Datadog. Its pricing plans are primarily based on the number of events or users per month.

  6. Use cases and target audience: Datadog caters to operations teams, providing comprehensive monitoring and observability solutions for infrastructure and applications. It is suitable for organizations with complex architectures and large-scale deployments. Sentry, on the other hand, is primarily targeted towards developers and engineering teams who want to capture and track errors and exceptions in code. It is particularly useful during development and testing phases to identify and fix issues early on.

In Summary, Datadog is a comprehensive monitoring tool focusing on metrics, logs, and alerts, while Sentry is primarily an error and exception tracking tool for developers. Datadog provides extensive monitoring capabilities and scalability, whereas Sentry offers rich error-context and easy integration into codebases for quicker debugging and issue resolution.

Advice on Datadog and Sentry
Farzeem Diamond Jiwani
Software Engineer at IVP · | 8 upvotes · 1.4M views
Needs advice
on
AppDynamicsAppDynamicsDatadogDatadog
and
DynatraceDynatrace

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!

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Needs advice
on
DatadogDatadogNew RelicNew Relic
and
SysdigSysdig

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?

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Replies (3)
Recommends
on
DatadogDatadog

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!

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Maik Schröder
Recommends
on
InstanaInstana

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.

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Attila Fulop
Management Advisor at artkonekt · | 2 upvotes · 317K views

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

https://docs.newrelic.com/docs/accounts/accounts-billing/new-relic-one-pricing-billing/new-relic-one-pricing-billing

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.

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Decisions about Datadog and Sentry

I essentially inherited a Shopify theme that was originally created by an agency. After discovering a number of errors being thrown in the Dev Console just by scrolling through the website, I needed more visibility over any errors happening in the field. Having used both Sentry and TrackJS, I always got lost in the TrackJS interface, so I felt more comfortable introducing Sentry. The Sentry free tier is also very generous, although it turns out the theme threw over 15k errors in less than a week.

I highly recommend setting up error tracking from day one. Theoretically, you should never need to upgrade from the free tier if you're keeping on top of the errors...

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Attila Fulop

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.

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Benoit Larroque
Principal Engineer at Sqreen · | 4 upvotes · 415.1K views

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

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Pros of Datadog
Pros of Sentry
  • 139
    Monitoring for many apps (databases, web servers, etc)
  • 107
    Easy setup
  • 87
    Powerful ui
  • 84
    Powerful integrations
  • 70
    Great value
  • 54
    Great visualization
  • 46
    Events + metrics = clarity
  • 41
    Notifications
  • 41
    Custom metrics
  • 39
    Flexibility
  • 19
    Free & paid plans
  • 16
    Great customer support
  • 15
    Makes my life easier
  • 10
    Adapts automatically as i scale up
  • 9
    Easy setup and plugins
  • 8
    Super easy and powerful
  • 7
    In-context collaboration
  • 7
    AWS support
  • 6
    Rich in features
  • 5
    Docker support
  • 4
    Cute logo
  • 4
    Source control and bug tracking
  • 4
    Monitor almost everything
  • 4
    Cost
  • 4
    Full visibility of applications
  • 4
    Simple, powerful, great for infra
  • 4
    Easy to Analyze
  • 4
    Best than others
  • 4
    Automation tools
  • 3
    Best in the field
  • 3
    Free setup
  • 3
    Good for Startups
  • 3
    Expensive
  • 2
    APM
  • 237
    Consolidates similar errors and makes resolution easy
  • 121
    Email Notifications
  • 108
    Open source
  • 84
    Slack integration
  • 71
    Github integration
  • 49
    Easy
  • 44
    User-friendly interface
  • 28
    The most important tool we use in production
  • 18
    Hipchat integration
  • 17
    Heroku Integration
  • 15
    Good documentation
  • 14
    Free tier
  • 11
    Self-hosted
  • 9
    Easy setup
  • 7
    Realiable
  • 6
    Provides context, and great stack trace
  • 4
    Feedback form on error pages
  • 4
    Love it baby
  • 3
    Gitlab integration
  • 3
    Filter by custom tags
  • 3
    Super user friendly
  • 3
    Captures local variables at each frame in backtraces
  • 3
    Easy Integration
  • 1
    Performance measurements

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Cons of Datadog
Cons of Sentry
  • 19
    Expensive
  • 4
    No errors exception tracking
  • 2
    External Network Goes Down You Wont Be Logging
  • 1
    Complicated
  • 12
    Confusing UI
  • 4
    Bundle size

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What is Datadog?

Datadog is the leading service for cloud-scale monitoring. It is used by IT, operations, and development teams who build and operate applications that run on dynamic or hybrid cloud infrastructure. Start monitoring in minutes with Datadog!

What is Sentry?

Sentry’s Application Monitoring platform helps developers see performance issues, fix errors faster, and optimize their code health.

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What are some alternatives to Datadog and Sentry?
New Relic
The world’s best software and DevOps teams rely on New Relic to move faster, make better decisions and create best-in-class digital experiences. If you run software, you need to run New Relic. More than 50% of the Fortune 100 do too.
Splunk
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
Prometheus
Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.
Grafana
Grafana is a general purpose dashboard and graph composer. It's focused on providing rich ways to visualize time series metrics, mainly though graphs but supports other ways to visualize data through a pluggable panel architecture. It currently has rich support for for Graphite, InfluxDB and OpenTSDB. But supports other data sources via plugins.
AppDynamics
AppDynamics develops application performance management (APM) solutions that deliver problem resolution for highly distributed applications through transaction flow monitoring and deep diagnostics.
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