Datadog and Splunk Observability Cloud compete in the digital operations monitoring and management category. Datadog shows a competitive edge due to its seamless integrations and comprehensive dashboards that minimize additional infrastructure needs, whereas Splunk holds potential for enterprises heavily reliant on SAP applications.
Features: Datadog offers sharable dashboards, integration support across diverse platforms, and dynamic hosted environments ensuring infrastructure independence. Users benefit from its flexible dashboards and visualization tools. Splunk Observability Cloud focuses on robust monitoring above SAP applications and data analysis across various enterprise environments.
Room for Improvement: Datadog could enhance its dashboard sharing options and stabilize its cost model and API usage. Concerns about database monitoring are common. Splunk Observability Cloud requires optimization for large environments, faster search capabilities, and better integrations for real-time data processing while aiming to refine user interface friendliness and documentation.
Ease of Deployment and Customer Service: Datadog facilitates smooth deployment in public and hybrid clouds with generally responsive support teams, although feedback on support quality varies. Installation is straightforward with robust resources. Splunk Observability Cloud is commended for its supportive service, yet some technical deployment and usage support improvements are indicated. Both solutions maintain flexible cloud environment operations.
Pricing and ROI: Datadog uses a pay-as-you-use model requiring careful planning to manage costs, which can be perceived as high with added features but offers strong ROI due to capability coverage. Splunk Observability Cloud has competitive yet costly licensing tied to data usage, where higher pricing is noted, but effective ROI stems from its comprehensive issue detection and time-saving capabilities.
Using Splunk has saved my organization about 30% of our budget compared to using multiple different monitoring products.
Anyone working in front-end management should recognize the market price to see the true value of end-user monitoring.
I have definitely seen a return on investment with Splunk Observability Cloud, particularly through how fast it has grown and how comfortable other teams are in relying on its outputs for monitoring and observability.
On a scale of 1 to 10, the customer service and technical support deserve a 10.
They have consistently helped us resolve any issues we've encountered.
They often require multiple questions, with five or six emails to get a response.
We've used the solution across more than 250 people, including engineers.
As we are a growing company transitioning all our applications to the cloud, and with the increasing number of cloud-native applications, Splunk Observability Cloud will help us achieve digital resiliency and reduce our mean time to resolution.
I would rate its scalability a nine out of ten.
I would rate its stability a nine out of ten.
We rarely have problems accessing the dashboard or the page.
Unlike NetScout or regular agents for APM, RUM has many problems during the POC phase because customer environments vary widely.
The documentation is adequate, but team members coming into a project could benefit from more guided, interactive tutorials, ideally leveraging real-world data.
In future updates, I would like to see AI features included in Datadog for monitoring AI spend and usage to make the product more versatile and appealing for the customer.
There should be a clearer view of the expenses.
The out-of-the-box customizable dashboards in Splunk Observability Cloud are very effective in showcasing IT performance to business leaders.
The next release of Splunk Observability Cloud should include a feature that makes it so that when looking at charts and dashboards, and also looking at one environment regardless of the product feature that you're in, APM, infrastructure, RUM, the environment that is chosen in the first location when you sign into Splunk Observability Cloud needs to stay persistent all the way through.
There is room for improvement in the alerting system, which is complicated and has less documentation available.
The setup cost for Datadog is more than $100.
Splunk is a bit expensive since it charges based on the indexing rate of data.
It is expensive, especially when there are other vendors that offer something similar for much cheaper.
It appears to be expensive compared to competitors.
Our architecture is written in several languages, and one area where Datadog particularly shines is in providing first-class support for a multitude of programming languages.
The technology itself is generally very useful.
Splunk provides advanced notifications of roadblocks in the application, which helps us to improve and avoid impacts during high-volume days.
For troubleshooting, we can detect problems in seconds, which is particularly helpful for digital teams.
It offers unified visibility for logs, metrics, and traces.
Product | Market Share (%) |
---|---|
Datadog | 7.4% |
Splunk Observability Cloud | 2.0% |
Other | 90.6% |
Company Size | Count |
---|---|
Small Business | 78 |
Midsize Enterprise | 42 |
Large Enterprise | 82 |
Company Size | Count |
---|---|
Small Business | 20 |
Midsize Enterprise | 10 |
Large Enterprise | 43 |
Datadog integrates extensive monitoring solutions with features like customizable dashboards and real-time alerting, supporting efficient system management. Its seamless integration capabilities with tools like AWS and Slack make it a critical part of cloud infrastructure monitoring.
Datadog offers centralized logging and monitoring, making troubleshooting fast and efficient. It facilitates performance tracking in cloud environments such as AWS and Azure, utilizing tools like EC2 and APM for service management. Custom metrics and alerts improve the ability to respond to issues swiftly, while real-time tools enhance system responsiveness. However, users express the need for improved query performance, a more intuitive UI, and increased integration capabilities. Concerns about the pricing model's complexity have led to calls for greater transparency and control, and additional advanced customization options are sought. Datadog's implementation requires attention to these aspects, with enhanced documentation and onboarding recommended to reduce the learning curve.
What are Datadog's Key Features?In industries like finance and technology, Datadog is implemented for its monitoring capabilities across cloud architectures. Its ability to aggregate logs and provide a unified view enhances reliability in environments demanding high performance. By leveraging real-time insights and integration with platforms like AWS and Azure, organizations in these sectors efficiently manage their cloud infrastructures, ensuring optimal performance and proactive issue resolution.
Splunk Observability Cloud offers sophisticated log searching, data integration, and customizable dashboards. With rapid deployment and ease of use, this cloud service enhances monitoring capabilities across IT infrastructures for comprehensive end-to-end visibility.
Focused on enhancing performance management and security, Splunk Observability Cloud supports environments through its data visualization and analysis tools. Users appreciate its robust application performance monitoring and troubleshooting insights. However, improvements in integrations, interface customization, scalability, and automation are needed. Users find value in its capabilities for infrastructure and network monitoring, as well as log analytics, albeit cost considerations and better documentation are desired. Enhancements in real-time monitoring and network protection are also noted as areas for development.
What are the key features?In industries, Splunk Observability Cloud is implemented for security management by analyzing logs from detection systems, offering real-time alerts and troubleshooting for cloud-native applications. It is leveraged for machine data analysis, improving infrastructure visibility and supporting network and application performance management efforts.
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