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.
"The most valuable features are logging, the extensive set of integrations, and easy jumpstart."
"Datadog has so far been a breeze to use and set up."
"Datadog is easy to use and easy to deploy. It's a better solution compared to others on the market in terms of being budget friendly for our customers."
"Having a clear view, not only of our infrastructure but our apps and services as well, has brought a great added value to our customers."
"It is easy to navigate the menu and create tests."
"I find the greatest feature is being able to search across logs from various microservices."
"Going from viewing a metric to creating a monitor alerting on a metric is very easy."
"The fact that everything is under a single pane of glass is really valuable, as developers don't have to spend their time copying correlation IDs across tools to find what they need."
"It's easy to use."
"Google's technical support is very good."
"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."
"We find the solution to be stable."
"I like the monitoring feature."
"Provides visibility into the performance uptime."
"The cloud login enables us to get our logs from the different platforms that we currently use."
"Our company has a corporate account for Google Cloud and so our systems and clusters integrate really well."
More Google Cloud's operations suite (formerly Stackdriver) Pros →
"We need to learn more about the session reply feature inside of DD."
"Federated views for Datadog dashboards are critical as large companies utilize multiple instances of the product and cannot link the metrics or correlate the metrics together. This stunts the usage of Datadog."
"For three to four months, we have been experiencing real-time delays. For example, if we're monitoring incoming traffic, the real-time status should be displayed up to a certain point. However, due to delays or issues with Datadog, the real-time data might only be updated at an earlier time. We are experiencing consistent delays in data updates from Datadog, with the most recent data often being delayed by about an hour. This issue has been ongoing for the past four months."
"The more tools that they can build that allow you to run AWX playbooks, or other similar fixes, would benefit clients greatly."
"While I like the ease of use, when compared with Tenable Nessus they could still improve their usability."
"The correlation between the logs and the metrics needs improvement as most cases, we might use another logging tool (that is cheaper in cost) which we then have to link together."
"Its pricing model can be improved. Its settings should be improved for a better understanding of billing. They should also provide some alerts when there is an increase in the usage. For example, if there is 20% more increase from one week to another, the customer should get an alert."
"The way data is represented can be limiting. When I first tried it out a long time ago, you could graph a metric and another metric, and they'd overlay, but you couldn't take the ratio between the two."
"The logging functionality could be better."
"The product provides minimal metrics that are insufficient."
"Lacking sufficient operations documentation."
"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."
"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."
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, Grafana and New Relic. 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.