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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

    MongoDB

    Score8.8 out of 10
    N/AMongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.

    $0.10

    million reads

    Pricing
    DatadogMongoDB
    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
    Shared
    $0
    per month
    Serverless
    $0.10million reads
    million reads
    Dedicated
    $57
    per month
    Offerings
    Pricing Offerings
    DatadogMongoDB
    Free Trial
    YesYes
    Free/Freemium Version
    YesYes
    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).Fully managed, global cloud database on AWS, Azure, and GCP
    More Pricing Information
    Community Pulse
    DatadogMongoDB
    Considered Both Products
    Datadog
    No answer on this topic
    MongoDB
    Chose MongoDB
    MongoDB and Cassandra are both database system from the NoSQL family. MongoDB can be used in lots of use cases while Cassandra has a specific usage. There are some features that MongoDB provides efficiently while Cassandra doesn't and vice-versa. Like, you can update the data …
    Incentivized
    Key User Insights
    Would buy again
    94%
    Would buy again
    50 Answers
    100%
    Would buy again
    12 Answers
    Delivers good value for the price
    93%
    Delivers good value for the price
    41 Answers
    100%
    Delivers good value for the price
    12 Answers
    Happy with the feature set
    98%
    Happy with the feature set
    52 Answers
    100%
    Happy with the feature set
    12 Answers
    Lived up to sales and marketing promises
    97%
    Lived up to sales and marketing promises
    32 Answers
    100%
    Lived up to sales and marketing promises
    9 Answers
    Implementation went as expected
    97%
    Implementation went as expected
    36 Answers
    100%
    Implementation went as expected
    12 Answers
    Features
    DatadogMongoDB
    Monitoring Tasks
    Comparison of Monitoring Tasks features of Datadog and MongoDB
    Feature
    Datadog
    7.9
    2 Ratings
    6% below category average
    MongoDB
    -
    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 MongoDB
    Feature
    Datadog
    6.1
    1 Ratings
    12% below category average
    MongoDB
    -
    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 MongoDB
    Feature
    Datadog
    8.2
    2 Ratings
    3% above category average
    MongoDB
    -
    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 MongoDB
    Feature
    Datadog
    6.7
    1 Ratings
    9% below category average
    MongoDB
    -
    Ratings
    Data backup and recovery6.41 Ratings00 Ratings
    Antivirus and malware management7.31 Ratings00 Ratings
    Administrator access control6.41 Ratings00 Ratings
    NoSQL Databases
    Comparison of NoSQL Databases features of Datadog and MongoDB
    Feature
    Datadog
    -
    Ratings
    MongoDB
    10.0
    39 Ratings
    16% above category average
    Performance00 Ratings10.039 Ratings
    Availability00 Ratings10.039 Ratings
    Concurrency00 Ratings10.039 Ratings
    Security00 Ratings10.039 Ratings
    Scalability00 Ratings10.039 Ratings
    Data model flexibility00 Ratings10.039 Ratings
    Deployment model flexibility00 Ratings10.038 Ratings
    Best Alternatives
    DatadogMongoDB
    Small Businesses
    Amazon CloudWatch
    Score7.8 out of 10
    IBM Cloudant
    Score7.4 out of 10
    Medium-sized Companies
    LogicMonitor
    Score8.9 out of 10
    IBM Cloudant
    Score7.4 out of 10
    Enterprises
    ManageEngine Site24x7
    Score10 out of 10
    IBM Cloudant
    Score7.4 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    DatadogMongoDB
    Likelihood to Recommend
    8.9
    (65 ratings)
    10.0
    (79 ratings)
    Likelihood to Renew
    4.3
    (2 ratings)
    10.0
    (67 ratings)
    Usability
    8.7
    (44 ratings)
    10.0
    (15 ratings)
    Availability
    -
    (0 ratings)
    9.0
    (1 ratings)
    Support Rating
    5.0
    (7 ratings)
    9.6
    (13 ratings)
    Implementation Rating
    1.0
    (1 ratings)
    8.4
    (2 ratings)
    User Testimonials
    DatadogMongoDB
    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
    Read full review
    MongoDB
    If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.
    Incentivized
    Read full review
    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
    Read full review
    MongoDB
    • Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
    • You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
    • Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.
    Incentivized
    Read full review
    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
    Read full review
    MongoDB
    • An aggregate pipeline can be a bit overwhelming as a newcomer.
    • There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
    • Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.
    Incentivized
    Read full review
    Likelihood to Renew
    Datadog
    Definitely will not revisit after our issues and, in my opinion, poor support.
    Incentivized
    Read full review
    MongoDB
    I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.
    Incentivized
    Read full review
    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
    Read full review
    MongoDB
    NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.
    Incentivized
    Read full review
    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
    Read full review
    MongoDB
    Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.
    Incentivized
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    Implementation Rating
    Datadog
    Documentation was difficult to work through, rollout was catastrophic (completely outage)
    Incentivized
    Read full review
    MongoDB
    While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.
    Incentivized
    Read full review
    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
    Read full review
    MongoDB
    We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.
    Read full review
    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
    Read full review
    MongoDB
    • Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
    • You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB
    Read full review
    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.

    MongoDB Screenshots

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