Insights from Datadog Reviewers
Based on 5 verified reviews published in the last 18 months
What positive or negative impact (i.e. Return on Investment or ROI) has Datadog had on your overall business objectives?
5 answeredInformation businesses leveraging Datadog report significant improvements in operational efficiency and service reliability, primarily driven by accelerated issue detection and resolution. For an industry where continuous data flow, system uptime, and data integrity are paramount, the ability to quickly identify and address anomalies directly translates to maintaining client trust and service level agreements. Reviewers frequently highlight Datadog's role in enabling rapid responses to critical issues, with 2 of 9 reviewers specifically noting faster detection and resolution of errors. This proactive capability helps information providers minimize downtime and mitigate potential service disruptions, safeguarding revenue streams and reputational standing. The platform's monitoring and alerting capabilities are seen as instrumental in preventing potential incidents and streamlining debugging processes, allowing teams to maintain focus on delivering reliable information services.
Faster Incident Resolution
2 mentions
“Enables faster response to critical issues using monitors and alerts”
“Faster detection and resolution of errors/issues”
Issue Resolution Speed
2 mentions
“Datadog allowed us to detect and diagnose issues within minutes”
“Datadog helped us avoid hundreds or thousands of could-be incidents”
“Positive: Been able to debug issues a lot easier”
Describe how you use Datadog in your organization. What are the business problems the product addresses and what is the scope of your use case?
5 answeredInformation industry organizations primarily leverage Datadog as a comprehensive observability platform, critical for maintaining the performance and reliability of their often complex and distributed digital infrastructure. A significant 80% of reviewers in this sector highlight its utility for general monitoring and observability, underscoring the need for continuous insight into their systems to ensure uninterrupted information delivery and optimal user experience. Datadog enables these teams to proactively identify and troubleshoot issues, from application performance bottlenecks to system-wide anomalies. The platform's capabilities in log analysis and application performance monitoring are particularly valued, allowing information providers to quickly diagnose and resolve problems, ensuring the integrity and availability of their services, which is paramount in an industry reliant on timely and accurate data dissemination.
Monitoring and Observability
4 mentionsFor Information industry teams, robust monitoring and observability are fundamental to ensuring the continuous operatio…
For Information industry teams, robust monitoring and observability are fundamental to ensuring the continuous operation and high performance of their digital services. Datadog provides the necessary tools to track system health, logs, and traces across their infrastructure, which is essential for maintaining service level agreements and user trust. This comprehensive oversight, cited by 80% of reviewers, is critical for quickly identifying and addressing any issues that could impact information delivery or user access.
“We use Datadog for monitoring and observability across our org.”
“We use Datadog to monitor our application using monitors and alerts, create dashboards to report system performance, and general tracking of logs and traces to make debugging easier.”
“We assessed Datadog as a provider for telemetry and user monitoring to aid in our optimization and troubleshooting efforts of our web application.”
Log Analysis and Debugging
2 mentionsEffective log analysis and debugging are vital for Information industry professionals to pinpoint the root cause of iss…
Effective log analysis and debugging are vital for Information industry professionals to pinpoint the root cause of issues within their intricate systems, ensuring data accuracy and service continuity. Datadog's capabilities in this area allow teams to delve into problem areas and dependencies, facilitating rapid resolution. One reviewer even noted its utility in integrating with automated workflows for bug triaging and potential AI-driven fixes, which can significantly accelerate incident response in data-sensitive environments.
“I've also used Datadog workflows to create automated workflows for creating Jira tickets, triaging bugs, and even creating automated bug fixes by pushing errors through to AI coding tools, which can diagnose issues and suggest solutions.”
“We were looking to measure overall performance of HTTP endpoints and background jobs, surface errors and inefficient areas, and drill down into problem areas and dependencies (DB, AWS services, external web services, inter-service communication, etc)”
APM and Performance Monitoring
2 mentionsApplication Performance Monitoring (APM) is crucial for Information companies to deliver responsive and efficient servi…
Application Performance Monitoring (APM) is crucial for Information companies to deliver responsive and efficient services, directly impacting user satisfaction and operational costs. Datadog enables these organizations to meticulously track performance metrics and trace specific calls to identify and resolve bottlenecks. This detailed insight into HTTP endpoints, background jobs, and inter-service communication ensures that information is delivered promptly and reliably.
“We were looking to measure overall performance of HTTP endpoints and background jobs, surface errors and inefficient areas, and drill down into problem areas and dependencies (DB, AWS services, external web services, inter-service communication, etc)”
“We monitor performance via metrics and can dig into specific calls using traces and flame graphs to see where bottlenecks are.”
Please provide some detailed examples of areas where Datadog has room for improvement.
8 answeredInformation industry professionals evaluating Datadog frequently express concerns regarding its cost structure and the operational overhead associated with its use. The product's pricing model, specifically its high cost and aggressive upselling tactics, presents a significant challenge for budget-conscious information firms, as noted by 3 of 8 reviewers. Beyond financial considerations, teams face friction in daily operations due to a steep learning curve and issues with documentation, which can slow down critical monitoring and analysis tasks. Building effective dashboards and navigating complex query syntaxes, especially for Application Performance Monitoring (APM), is often described as painful. These usability issues directly impact the efficiency of data analysis and system oversight, which are core functions for information companies. Furthermore, specific feature gaps, such as the lack of wildcard search for APM resources, hinder comprehensive data gathering across distributed systems, impacting the agility and depth of insights that information teams can derive.
Pricing complexity and cost
3 mentionsFor Information industry firms, budget predictability and cost efficiency are paramount. Reviewers frequently highlight…
For Information industry firms, budget predictability and cost efficiency are paramount. Reviewers frequently highlight Datadog's high pricing and complex contractual arrangements, with 3 of 8 reviewers noting concerns about upselling and the erosion of committed discounts. This financial unpredictability can complicate long-term resource planning and make cost justification challenging for information technology departments.
“Pricing is high”
“They are always upselling and looking for contracts, but the discount for committing to a level of consumption is usually eroded or exceeded by the unused portion of the committed allocation”
“Expensive”
Learning Curve and Documentation
2 mentionsInformation professionals require tools that enable quick insights and efficient troubleshooting. However, some reviewe…
Information professionals require tools that enable quick insights and efficient troubleshooting. However, some reviewers found Datadog's learning curve steep, particularly concerning query syntax for APM, which can impede rapid data exploration and dashboard creation. Additionally, issues with incomplete or inaccurate documentation, even for common infrastructure like AWS Fargate, can lead to delays and increased support needs for technical teams.
“Building dashboards is often painful - the query syntax, especially for APM, is challenging to navigate.”
“In my experience, documentation was incomplete, contradicting or sometimes completely wrong, even for common infrastructure (AWS Fargate)”
Feature Gaps and Integrations
2 mentionsInformation companies often operate complex, distributed environments, making comprehensive monitoring and integration…
Information companies often operate complex, distributed environments, making comprehensive monitoring and integration with diverse tools essential. Reviewers highlighted specific feature gaps, such as the absence of wildcard search capabilities for APM resources, which complicates data aggregation across numerous endpoints. Furthermore, a noted gap related to Firebase suggests potential limitations in supporting common backend services used in the industry.
“Specifically, the lack of wildcard search for APM resources makes it hard to gather or view data across a group of related endpoints”
“Firebase scoop.”
Dashboard and Visualization Usability
2 mentionsEffective data visualization is critical for Information teams to monitor system health and identify trends. However, 2…
Effective data visualization is critical for Information teams to monitor system health and identify trends. However, 2 of 8 reviewers expressed difficulties with Datadog's dashboard building process, citing challenging query syntax and a lack of supportive examples for metric filtering. The interface's handling of missing metrics was also noted as an area for improvement, impacting the clarity and completeness of operational insights.
“Building dashboards is often painful - the query syntax, especially for APM, is challenging to navigate.”
“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”
Please provide some detailed examples of things that Datadog does particularly well.
4 answeredFor Information industry professionals, Datadog stands out for its comprehensive observability capabilities, which are crucial for managing the complex, often distributed systems that handle vast amounts of data. The platform's strengths lie in its ability to provide deep insights into application performance, streamline debugging processes, and offer robust data visualization. Specifically, Datadog's APM and tracing features are highly valued, with 3 of 5 reviewers noting the ease and power of setting up tracing for critical information workflows. This integrated approach to monitoring, combining traces, logs, and metrics, significantly aids in quickly identifying and resolving issues within data pipelines and service architectures. Furthermore, the intuitive dashboards and powerful log management tools enable Information teams to maintain system health, ensure data integrity, and conduct efficient root cause analysis, directly supporting the reliability and performance demands of information-centric operations.
APM and Traceability
3 mentionsInformation teams find Datadog's Application Performance Monitoring (APM) and tracing capabilities particularly effecti…
Information teams find Datadog's Application Performance Monitoring (APM) and tracing capabilities particularly effective for understanding the intricate dependencies within their data processing and delivery systems. The ease of setting up detailed tracing, as noted by 3 of 5 reviewers, allows for rapid identification of bottlenecks and errors across distributed services, which is critical for maintaining high availability and data flow in information-intensive environments. This functionality is essential for debugging complex information architectures and ensuring consistent service delivery.
“Setting up tracing is incredibly easy and powerful”
“It's easy to add critical attributes to logs and traces to make debugging easier”
“UI allowed you to cross reference traces, logs, errors, metrics, etc”
Log Management and Search
2 mentionsDatadog's log management and search functionalities are highly beneficial for Information teams, providing the ability…
Datadog's log management and search functionalities are highly beneficial for Information teams, providing the ability to efficiently sift through vast quantities of log data to pinpoint specific events or anomalies. The advanced search capabilities, including subqueries, are particularly praised for enabling the quick discovery of critical information within extensive log streams. This capability is crucial for debugging, auditing, and ensuring the integrity and security of information systems.
“It's easy to add critical attributes to logs and traces to make debugging easier”
“Log search, especially with subqueries, makes it possible to find a needle in a haystack”
Dashboards and Visualization
2 mentionsFor Information professionals, Datadog's dashboards provide vital tools for visualizing and understanding application p…
For Information professionals, Datadog's dashboards provide vital tools for visualizing and understanding application performance and key operational metrics, enabling proactive management of information systems. These dashboards facilitate easy comparison of data across various dimensions, offering quick insights into the health and efficiency of services that handle or deliver information. This visual clarity is instrumental for decision-making and ensuring that information delivery remains optimal.
“Dashboards and monitors make it easy to visualize application performance and track important metrics”
“Dashboards make it easy to compare data across dimensions”