Datadog vs. GoodData.AI

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.

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I think it works nicely for shops that want the analytical power and are ok to host their own infrastructure for the data and etl. For smaller operations with limited budgets but still high demand for analytical features the math may not work out.

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• 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.

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• The source datasets are often complex, semi-structured and un-linked to key entities. With GoodData, all of these datasets are unified to serve as a central semantic data model layer, building into a galaxy schema with dimensions, bridge, and facts, which then forms the backbone that powers the [...] data intelligence cloud. Building insights and dashboards become a much easier task once the underlying data model is designed. GoodData enforces certain best practices as a BI tool, which must be adhered to get the true value of the raw data. For e.g. the source FDA dashboard may just show inspection data but the Site Profile dashboard built on GoodData goes beyond the standard information and shows more insight into site risk scores and can be drilled into details. There is blog written on this topic: [...].
• GoodData provides a rich collection of visualization options that help us create compelling story-telling via dashboards. Being well-prepared for FDA inspections is essential for maintaining product quality, regulatory compliance, and avoiding serious business setbacks. FDA inspections are critical events that can shape a company’s market access and reputation. The FDA itself offers the FDA Data Dashboard, but it doesn’t make every document available. There is a blog written on this topic: [...].
• Medical devices and technologies do not stop evolving after they receive regulatory approval. Once a product hits the market, it faces real-world usage, compliance challenges, and an array of regulatory scrutiny. Managing these postmarket dynamics is critical to a product’s long-term success and patient safety. However, many companies struggle to keep track of relevant events across a product’s markets, from adverse event reports to changing regulations. Postmarket Intelligence developed on GoodData platform enables us to solve that problem. It empowers MedTech companies to efficiently monitor, assess, and act on postmarket data—saving time, improving decision-making, and ensuring compliance with industry standards. Anyone who is used to trying to get the data they need from the various FDA, and other regulatory agency websites, knows that collecting, cleaning, and structuring that data takes hours. And that’s before any analysis can get done. We enable customers to free up time to focus only on the high-value analysis and subsequent recommendations to leadership, rather than wrangling the data.
• The data pipeline refresh that is provided by GoodData Platform is also quite useful from data engineering perspective. The Automated Data Distribution v2 or commonly called as ADD refresh follows a set pattern of identifying the analytical data model through output stage which helps abstract the complex table definition to simpler views that can help with quick rebuild at the data warehouse level while loading the data into GoodData's ADS storage layer. The import first way of loading data into GoodData's cloud storage, followed by querying for any aggregations or metrics on the GoodData analyzer, makes this simple and fast.
• GoodData's latest product i.e. Cloud also offers several good features like Analytics as Code which helps software engineering teams follow a code-first approach to analytics, where building insights, dashboards or even datasets can be done in YAML templates or serviced by REST APIs. This is particularly forward thinking in the modern technology stack and evolving industry requirements. These provide seamless integration options to front-end and backend code, embedded analytics with multiple choices from HTML to React based workloads. At [...], we are currently exploring most of these features while planning for a future migration from Platform to Cloud.

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• 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

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• Good Data is already have certain customizable options. However, having more flexibility in customizing reports and dashboards & control over the visual aspects would enhance the overall user experience.
• To make Good Data even more powerful tool, improving the speed and responsiveness of the tool, especially during data-intensive tasks, would be a significantly helpful.
• For new users, the interface can be made more user friendly which would promote easy navigation through features of tool.

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Definitely will not revisit after our issues and, in my opinion, poor support.

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Because gooddata really helps us in processing data to make reports or dashboards. So we are very satisfied when we use it. What we like is the flexible use of charts. We change at will the use of charts to display in reports or dashboards. Thank you Gooddata for helping companies like us who need flexibility in usage

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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.

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From a customer perspective it is incredibly usable. We have more users building their own reports that would normally need custom work from our support team. The back end can be daunting when trying to configure things like new data elements or push changes to a report to all existing customers.

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We are approximately one month since go-live. There has been one short outage.

I'm generally impressed with how fast it reflects so much data.

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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.

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Support team has been highly responsive and helpful from our first initial deployment to present day. They engage and work with us. know when to escalate for more challenging problems. They also follow up. Overall have had a very good experience with support

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Petr was a rock star - patient, knowledgeable, clear and easy to work with.

GoodData implementation team was professional and courteous

Documentation was difficult to work through, rollout was catastrophic (completely outage)

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info

Implementations are hard and we had limited technical resources. We relied too heavily on GD care team. When we found technical gaps, they weren't simple to overcome

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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.

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Invited by TrustRadius (TR) on Vendor's Behalf

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GoodData comparing to other platform is very easy to use, customer support and on-boarding support. Set of features, speed of integration in our platform. Also great benefit for us was very competetive pricing.

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We never had any issues with scalability, other than being limited by workspaces

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• 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.

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• I personally pushed our management to get GoodData implemented, and there on we have been making much more profits than we ever did!
• Last month we made a decision using the platform and withing a short span of time our ROI gets 7X.
• We also made a marketing spend of $100,000 every quater using the insights and metrics, and we are really happy with the returs.

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Invited by the Vendor

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info