We performed a comparison between Datadog and Google Cloud's operations suite (formerly Stackdriver) based on our users’ reviews in five categories. After reading all of the collected data, you can find our conclusion below.
Features: Users have favorable things to say in regards to Datadog's ease of use, convenient setup, useful dashboards, error reporting, log centralization, and troubleshooting features as well as the user-friendliness for development teams. It has a nice interface and is flexible. Google Cloud's operations suite is praised for its easy setup and monitoring capabilities. Datadog could enhance its usability, integration, user interface, learning curve, external website monitoring, SSL security, and setup complexity. Google Cloud's operations suite would benefit from extra metrics and tools, enhanced application logs, stability, improved logging functionality, and increased profiling capabilities.
Service and Support: The opinions about Datadog's customer service vary, with some users appreciating the quick and useful assistance they provide. However, there have been instances where support has been slow or unresponsive. Google Cloud's operations suite is known for its excellent technical support, although certain users have not required assistance from customer service.
Ease of Deployment: Datadog's initial setup is regarded as simple and uncomplicated, with help accessible from service providers or technical support. Google Cloud's operations suite (formerly Stackdriver) has a direct setup process managed by the DevOps team, with excellent documentation provided for assistance.
Pricing: Users have expressed mixed opinions regarding the setup cost of Datadog's product. Some find it to be expensive and confusing, and others feel that it is restrictive or unclear. Google Cloud's operations suite is viewed as a concern due to its pricing, although one user considers it to be very cheap.
ROI: Users have experienced varying levels of ROI with Datadog, with benefits such as time savings and reduced blind spots. On the other hand, Google Cloud's operations suite has consistently delivered a positive ROI for users.
Comparison Results: Datadog is the preferred choice when compared to Google Cloud's operations suite. Users appreciate Datadog's ease of use, convenient setup, useful dashboards, error reporting, log centralization, and troubleshooting features. They also value Datadog's user-friendliness for development teams, interface and integrations, flexibility, and observability.
"It has saved us a lot of trouble in implementation."
"Datadog provides tracing and logging, whereas Dynatrace focuses on tracing, and Splunk is more of a logging tool. Datadog's advantage is that we don't need two tools."
"The tools are powerful and intuitive to set up."
"The most valuable feature I have found is the elastic container service."
"It provides more cloud data. They tend to just get the way a service would be designed on the cloud."
"Even if we don't end up using Datadog, it revealed problems and optimizations to us that weren't obvious before."
"Datadog helps us detect issues early on and helps in troubleshooting."
"Datadog has clear dashboards and good documentation."
"Provides visibility into the performance uptime."
"Our company has a corporate account for Google Cloud and so our systems and clusters integrate really well."
"We find the solution to be stable."
"Google's technical support is very good."
"It's easy to use."
"The cloud login enables us to get our logs from the different platforms that we currently use."
"The most valuable feature is the multi-cloud integration, where there is support for both GCP and AWS."
"The features that I have found most valuable are its graphs - if I need any statistics, in Kubernetes or Kong level or VPN level, I can quickly get the reports."
More Google Cloud's operations suite (formerly Stackdriver) Pros →
"One area where I was really looking for improvement was the CSPM product line. I had really wanted to have team-level visibility for findings, since the team managing the resources has much more context and ability to resolve the issue, as the service owner. However, this has been added to the announcement in a recent keynote."
"Datadog could be improved if it could detect other software in a container or server."
"I'm still exploring the trial version, and it is fine. One thing that I haven't been able to figure out is how to retrieve a report. This is something that could be improved. I probably need to navigate to a place to access the reports."
"I'm not sure if Datadog can monitor K8s deployments in real-time. For instance, being able to see a deployment step by step visually. This would be helpful if there were any incidents during the deployment."
"Alerting timing should be improved to be more fine-tuned and exact."
"Datadog is so feature-rich that it is often hard to onboard new folks and tough to decide where to invest time."
"Since the Datadog platform has so many separate features, solving so many use cases, there are often inconsistencies in feature availability and interoperability between products."
"Datadog has a lot of documentation, but a lot of that documentation assumes you know how the service works, which can lead to confusion."
"It is difficult to estimate in advance how much something is going to cost."
"This solution could be improved if it offered the ability to analyze charts, such as a solution like Kibana."
"It could be more stable."
"If I want to track any round-trip or breakdowns of my response times, I'm not able to get it. My request goes through various levels of the Google Cloud Platform (GCP) and comes back to my client machine. Suppose that my request has taken 10 seconds overall, so if I want to break it down, to see where the delay is happening within my architecture, I am not able to find that out using Stackdriver."
"The logging functionality could be better."
"While we are satisfied with the overall performance, in certain cases we must add additional metrics and additional tools like Grafana and Dynatrace."
"It could be even more automated."
"The product provides minimal metrics that are insufficient."
More Google Cloud's operations suite (formerly Stackdriver) Cons →
More Google Cloud's operations suite (formerly Stackdriver) Pricing and Cost Advice →
Datadog is ranked 1st in Application Performance Monitoring (APM) and Observability with 137 reviews while Google Cloud's operations suite (formerly Stackdriver) is ranked 27th in Application Performance Monitoring (APM) and Observability with 9 reviews. Datadog is rated 8.6, while Google Cloud's operations suite (formerly Stackdriver) is rated 7.8. The top reviewer of Datadog writes "Very good RUM, synthetics, and infrastructure host maps". On the other hand, the top reviewer of Google Cloud's operations suite (formerly Stackdriver) writes "Good logging and tracing but does need more profiling capabilities". Datadog is most compared with Dynatrace, Azure Monitor, New Relic, AWS X-Ray and Amazon CloudWatch, whereas Google Cloud's operations suite (formerly Stackdriver) is most compared with AWS X-Ray, Azure Monitor, Amazon CloudWatch, New Relic and Grafana. See our Datadog vs. Google Cloud's operations suite (formerly Stackdriver) report.
See our list of best Application Performance Monitoring (APM) and Observability vendors, best Log Management vendors, and best Cloud Monitoring Software vendors.
We monitor all Application Performance Monitoring (APM) and Observability reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.