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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Datadog

    Score8.8 out of 10
    N/ADatadog is a monitoring service for IT, Dev and Ops teams who write and run applications at scale, and want to turn the massive amounts of data produced by their apps, tools and services into actionable insight.

    $18

    per month per host

    Git

    Score10 out of 10
    N/AN/AN/A
    Pricing
    DatadogGit
    Editions & Modules
    Log Management
    $1.27
    per month (billed annually) per host
    Infrastructure
    $15.00
    per month (billed annually) per host
    Standard
    $18
    per month per host
    Enterprise
    $27
    per month per host
    DevSecOps Pro
    $27
    per month per host
    APM
    $31.00
    per month (billed annually) per host
    DevSecOps Enterprise
    $41
    per month per host
    No answers on this topic
    Offerings
    Pricing Offerings
    DatadogGit
    Free Trial
    YesNo
    Free/Freemium Version
    YesNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeOptionalNo setup fee
    Additional DetailsDiscount available for annual pricing. Multi-Year/Volume discounts available (500+ hosts/mo).—
    More Pricing Information
    Features
    DatadogGit
    Monitoring Tasks
    Comparison of Monitoring Tasks features of Datadog and Git
    Feature
    Datadog
    7.9
    2 Ratings
    6% below category average
    Git
    -
    Ratings
    Remote monitoring8.22 Ratings00 Ratings
    Network device monitoring7.72 Ratings00 Ratings
    Multiple Server Monitoring7.72 Ratings00 Ratings
    Multi-device monitoring7.72 Ratings00 Ratings
    Automated alerts and notifications8.22 Ratings00 Ratings
    Management Tasks
    Comparison of Management Tasks features of Datadog and Git
    Feature
    Datadog
    6.1
    1 Ratings
    12% below category average
    Git
    -
    Ratings
    Patch Management7.31 Ratings00 Ratings
    Service configuration management6.41 Ratings00 Ratings
    Software and hardware inventory5.51 Ratings00 Ratings
    Policy-based automation5.51 Ratings00 Ratings
    Reporting
    Comparison of Reporting features of Datadog and Git
    Feature
    Datadog
    8.2
    2 Ratings
    3% above category average
    Git
    -
    Ratings
    Performance data reports8.22 Ratings00 Ratings
    Customizable reporting7.72 Ratings00 Ratings
    Data visualization8.62 Ratings00 Ratings
    Risk analysis8.22 Ratings00 Ratings
    Security
    Comparison of Security features of Datadog and Git
    Feature
    Datadog
    6.7
    1 Ratings
    9% below category average
    Git
    -
    Ratings
    Data backup and recovery6.41 Ratings00 Ratings
    Antivirus and malware management7.31 Ratings00 Ratings
    Administrator access control6.41 Ratings00 Ratings
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    Score8.9 out of 10
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    Score9.2 out of 10
    Enterprises
    ManageEngine Site24x7
    Score10 out of 10
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    Score7.5 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    DatadogGit
    Likelihood to Recommend
    8.9
    (65 ratings)
    10.0
    (36 ratings)
    Likelihood to Renew
    4.3
    (2 ratings)
    10.0
    (1 ratings)
    Usability
    8.7
    (44 ratings)
    9.0
    (1 ratings)
    Support Rating
    5.0
    (7 ratings)
    8.5
    (11 ratings)
    Implementation Rating
    1.0
    (1 ratings)
    9.0
    (1 ratings)
    User Testimonials
    DatadogGit
    Likelihood to Recommend
    Datadog
    Datadog may be better suited for teams that have a more out-of-the-box infrastructure, on the primary platforms Datadog supports. You may also have better results if you have a bigger team dedicated to devops and/or a bigger budget. We found that trying to adapt it to our use case (small team, .NET on AWS Fargate) wasn't feasible. We continually ran into roadblocks that required us to dig through documentation (and at times, having to figure out some documentation was wrong), go back and forth with support, and in my opinion, waste money on excessive and unintended usages due to opaque pricing models and inaccurate usage reports, as well as broken/non-functional rate sampling controls.
    Incentivized
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    Open Source
    GIT is good to be used for faster and high availability operations during code release cycle. Git provides a complete replica of the repository on the developer's local system which is why every developer will have complete repository available for quick access on his system and they can merge the specific branches that they have worked on back to the centralized repository. The limitations with GIT are seen when checking in large files.
    Incentivized
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    Pros
    Datadog
    • The thing which Datadog does really well, one of them are its broad range of services integrations and features which makes it one step observability solution for all. We can monitor all types of our application, infrastructure, hosts, databases etc with Datadog.
    • Its custom dashboard feature which helps us to visualize the data in a better way . It supports different types of charts through those charts we can create our dashboard more attractive.
    • Its AI powered alerting capability though that we can easily identify the root cause and also it has a low noise alerting capability which means it correlated the similar type of issues.
    Incentivized
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    Open Source
    • Ability to create branches off current releases to modify code that can be tested in a separate environment.
    • Each developer had their own local copy of branches so it minimizes mistakes being made.
    • Has a user-friendly UI called Git Gui that users can use if they do not like using the command line.
    • Conflicts are displayed nicely so that developers can resolve with ease.
    Incentivized
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    Cons
    Datadog
    • Alert windows cause lag in notifications (e.g. if the alert window is X errors in 1 hour, we won't get alerted until the end of the 1 hour range)
    • I would appreciate more supportive examples for how to filter and view metrics in the explorer
    • I would like a more clear interface for metrics that are missing in a time frame, rather than only showing tags/etc. for metrics that were collected within the currently viewed time frame
    Incentivized
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    Open Source
    • There can be quite a number of commands once you get to the advanced features and functionality of Git. Takes time to master.
    • Doesn't handle static assets (ie: videos, images, etc.) well. Although in the recent years, new functionality has been introduced to address this.
    • Many different GUIs, many people (including myself) opt to just use the command-line.
    Incentivized
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    Likelihood to Renew
    Datadog
    Definitely will not revisit after our issues and, in my opinion, poor support.
    Incentivized
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    Open Source
    Git has met all standards for a source control tool and even exceeded those standards. Git is so integrated with our work that I can't imagine a day without it.
    Incentivized
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    Usability
    Datadog
    There are so many features that it can be hard to figure out where you need to go for your own use case. For example, RUM monitoring us buried in a "Digital Experience" sidebar setting when this is one of our key use cases that I sometimes struggle to find in the application. It appears that ECS + Fargate monitoring was recently released which is great because we had to build a lambda reporting solution for ephemeral task monitoring. But this new feature was never on my radar until I starting clicking around the application.
    Incentivized
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    Open Source
    Git is easy to use most of the time. You mostly use a few commands like commiting, fetch/pull, and push which will get you by for most of time.
    Incentivized
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    Support Rating
    Datadog
    The support team usually gets it right. We did have a rather complicate issue setting up monitoring on a domain controller. However, they are usually responsive and helpful over chat. The downside would be I don’t think they have any phone support. If that is important to you this might not be a good fit.
    Incentivized
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    Open Source
    I am not sure what the official Git support channels are like as I have never needed to use any official support. Because Git is so popular among all developers now, it is pretty easy to find the answer to almost any Git question with a quick Google search. I've never had trouble finding what I'm looking for.
    Incentivized
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    Implementation Rating
    Datadog
    Documentation was difficult to work through, rollout was catastrophic (completely outage)
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    Open Source
    It's easy to set up and get going.
    Incentivized
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    Alternatives Considered
    Datadog
    Our logs are very important, and Datadog manages them exceptionally well. We frequently use Datadog services for our investigations. Use case: Monitor your apps, infrastructure, APIs, and user experience.


    Key features:


    Logs, metrics, and APM (Application Performance Monitoring)


    Real-time alerting and dashboards


    Supports Kubernetes, AWS, GCP, and other integrations


    RUM (Real User Monitoring) and Synthetics





    ✅ Best for backend, server, and distributed systems monitoring.
    Incentivized
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    Open Source
    I've used both Apache Subversion & Git over the years and have maintained my allegiance to Git. Git is not objectively better than Subversion. It's different.
    The key difference is that it is decentralized. With Subversion, you have a problem here: The SVN Repository may be in a location you can't reach (behind a VPN, intranet - etc), you cannot commit. If you want to make a copy of your code, you have to literally copy/paste it. With Git, you do not have this problem. Your local copy is a repository, and you can commit to it and get all benefits of source control. When you regain connectivity to the main repository, you can commit against it. Another thing for consideration is that Git tracks content rather than files. Branches are lightweight and merging is easy, and I mean really easy.
    It's distributed, basically every repository is a branch. It's much easier to develop concurrently and collaboratively than with Subversion, in my opinion. It also makes offline development possible. It doesn't impose any workflow, as seen on the above linked website, there are many workflows possible with Git. A Subversion-style workflow is easily mimicked.
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    Return on Investment
    Datadog
    • Saved us (time & money) from developing our own monitoring utilities that would pale in comparison
    • Alerts allow us to remedy issues before our customers even know about them
    • Tracking resource usage over time allows us to better plan for future needs, before it becomes a pain-point.
    Incentivized
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    Open Source
    • Git has saved our organization countless hours having to manually trace code to a breaking change or manage conflicting changes. It has no equal when it comes to scalability or manageability.
    • Git has allowed our engineering team to build code reviews into its workflow by preventing a developer from approving or merging in their own code; instead, all proposed changes are reviewed by another engineer to assess the impact of the code and whether or not it should be merged in first. This greatly reduces the likelihood of breaking changes getting into production.
    • Git has at times created some confusion among developers about what to do if they accidentally commit a change they decide later they want to roll back. There are multiple ways to address this problem and the best available option may not be obvious in all cases.
    Incentivized
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    ScreenShots

    Datadog Screenshots

    Screenshot of the out-of-the-box and customizable monitoring dashboards.Screenshot of Datadog's collaboration features, where users can discuss issues in-context with production data, annotate changes and notify their teams, see who responded to that alert before, and discover what was done to fix it.Screenshot of where Datadog unifies traces, metrics, and logs—the three pillars of observability.Screenshot of some of Datadog's 400+ built-in integrations.Screenshot of Datadog's Service Map, which decomposes an application into all its component services and draws the observed dependencies between these services in real timeScreenshot of centralized log data, pulled from any source.