Chronosphere vs Datadog comparison

Read 209 Datadog reviews

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97% willing to recommend

Chronosphere

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Executive SummaryUpdated on Oct 19, 2025

Datadog and Chronosphere compete in cloud monitoring solutions. Datadog appears to have the upper hand with broader feature availability and robust integration options.

Features: Datadog offers comprehensive monitoring, customizable dashboards, and extensive third-party integrations enabling easy monitoring consolidation across services. Chronosphere emphasizes high scalability, efficient data ingestion, and cost efficiency, reducing latency for large-scale data handling.

Ease of Deployment and Customer Service: Datadog has streamlined deployment, extensive documentation, and support services making setup straightforward for cloud environments. Chronosphere meets enterprise needs with tailored deployment options and strong support for complex deployments.

Pricing and ROI: Datadog's tiered pricing structure is perceived as strong value despite higher upfront costs due to feature depth. Chronosphere offers competitive pricing emphasizing low-cost scalability, resulting in favorable ROI for managing vast data volumes.

To learn more, read our detailed Application Performance Monitoring (APM) and Observability Report (Updated: November 2025).

Application Performance Monitoring (APM) and Observability

November 2025

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

Chronosphere

Ranking in Application Performance Monitoring (APM) and Observability

31st

Ranking in Log Management

31st

Ranking in AIOps

18th

Average Rating

9.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Datadog

Ranking in Application Performance Monitoring (APM) and Observability

1st

Ranking in Log Management

3rd

Ranking in AIOps

1st

Average Rating

8.6

Reviews Sentiment

7.0

Number of Reviews

209

Ranking in other categories

Network Monitoring Software (3rd), IT Infrastructure Monitoring (2nd), Container Monitoring (2nd), Cloud Monitoring Software (2nd), Cloud Security Posture Management (CSPM) (5th), AI Observability (1st)

Mindshare comparison

As of December 2025, in the Application Performance Monitoring (APM) and Observability category, the mindshare of Chronosphere is 0.6%, up from 0.3% compared to the previous year. The mindshare of Datadog is 6.0%, down from 9.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Application Performance Monitoring (APM) and Observability Market Share Distribution
Product	Market Share (%)
Datadog	6.0%
Chronosphere	0.6%
Other	93.4%

Application Performance Monitoring (APM) and Observability

Featured Reviews

Arvind Pant

Senior Data Engineer at DoorDash, Inc.

Monitors pipelines with real-time alerts and good documentation

It isn't very easy. It's not easy for everyone. It would be much easier if there could be a simpler version, like a data number version or an SQL version. It's hard to debug if you don't know the syntax. Also, I saw the Slack alerts feature, which is pretty cool, but I cannot customize my messages on the Slack alerts. It would be great if it were possible to tag people in the alerts. At DoorDash, we have hundreds of pipelines, and if something fails, I want to tag specific people so they can start working on the issue immediately.

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Dhroov Patel

Site Reliability Engineer at Grainger

Has improved incident response with better root cause visibility and supports flexible on-call scheduling

Datadog needs to introduce more hard limits to cost. If we see a huge log spike, administrators should have more control over what happens to save costs. If a service starts logging extensively, I want the ability to automatically direct that log into the cheapest log bucket. This should be the case with many offerings. If we're seeing too much APM, we need to be aware of it and able to stop it rather than having administrators reach out to specific teams. Datadog has become significantly slower over the last year. They could improve performance at the risk of slowing down feature work. More resources need to go into Fleet Automation because we face many problems with things such as the Ansible role to install Datadog in non-containerized hosts. We mainly want to see performance improvements, less time spent looking at costs, the ability to trust that costs will stay reasonable, and an easier way to manage our agents. It is such a powerful tool with much potential on the horizon, but cost control, performance, and agent management need improvement. The main issues are with the administrative side rather than the actual application.

Read full review

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The alerting features are good"

"The most valuable aspects of the product include the APM and profiler."

"The most valuable aspect of the solution is the APM."

"Our primary alerts, based on metrics and synthetic transactions, are the most used and relied upon for decreased MTTA/MTTR across all of our platforms. This is followed by deep log analysis that enables us to quickly and easily get to a preliminary root cause that someone on the infrastructure, platform or development teams can take and focus their attention on the precise target that Datadog revealed as the issue to be remediated."

"It has provided visibility with ease of implementation and allowed multiple teams to quickly onboard it."

"We like the distributed tracing and flame graphs for debugging. This has been invaluable for us during periods of high traffic or red alert conditions."

"Flame graphs are pretty useful for understanding how GraphQL resolves our federated queries when it comes to identifying slow points in our requests. In our microservice environment with 170 services."

"The solution is stable."

"The many dozens of integrations that the solution brings out of the box are excellent."

More Datadog pros

Cons

"It's not easy for everyone."

"Additional metrics should be included."

"I think Datadog can be improved by continually finding errors and making things easy to see and customize."

"Datadog could make their use cases more visible either through their docs or tutorial videos."

"When it comes to storing the logs with Datadog, I'm not sure why it costs so much to store gigabytes or terabytes of information when it's a fraction of the cost to do so myself."

"They need to offer better/more customization on what logs we get and making tracing possible on Edge runtime logs is a real requirement."

"When the logs are too big, and Datadog splits them, the JSON format breaks and it is not so useful for us."

"In some ways, the tool has a pretty steep learning curve. Discovering the various capabilities available, then learning how to utilize them for particular use cases can be challenging."

"The pricing should be less of a surprise."

More Datadog cons

Pricing and Cost Advice

Information not available

"Our licensing fees are paid on a monthly basis."

"Pricing seems reasonable. It depends on the size of your organization, the size of your infrastructure, and what portion of your overall business costs go toward infrastructure."

"Licensing is based on the retention period of logs and metrics."

"The pricing and licensing through AWS Marketplace has been good. It would be nice if it was cheaper, but their pricing is reasonable for what it is. Sometimes, for their newer features, they charge as if it's fully fleshed out, even though it is a newer feature and it may have less stuff than their other items."

"Datadog does not provide any free plans to use the solution. When I start with a proof of concept it would be sensible to have a free plan to test the tool and check whether it fits the requirements of the project. Before the production stage, it is always good to have a free plan with some limited features, number of requests, or logs."

"I am not satisfied with its licensing. Its payment is based on the exported data, and there was an explosion of the data for three or four weeks. My customer was not alerted, and there was no way for them to see that there has been an explosion of data. They got a big invoice for one or two months. The pricing model of Datadog is based on the data. The customer was quite surprised about not being alerted about this explosion of data. They should provide some kind of alert when there is an increase in usage."

"My advice is to really keep an eye on your overage costs, as they can spiral really fast."

"It is easy to run up a large bill, so become familiar with the cost of each piece of your bill and use the metrics they supply to estimate and monitor your bill."

More Datadog pricing and cost advice

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Top Industries

By visitors reading reviews

Transportation Company

15%

Retailer

11%

Financial Services Firm

10%

Computer Software Company

10%

Financial Services Firm

14%

Computer Software Company

13%

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	80
Midsize Enterprise	46
Large Enterprise	98

Questions from the Community

What needs improvement with Chronosphere?

What is your primary use case for Chronosphere?

I work as a data engineer, and we have many streaming pipelines. We use Chronosphere to monitor various metrics, such as how much data our pipeline is processing in each batch, the volume of incomi...

What advice do you have for others considering Chronosphere?

If you want to monitor pipelines and use something like Kafka or any streaming platform, Chronosphere is the best option for monitoring pipelines with real-time alerts. It is loosely coupled with y...

Any advice about APM solutions?

There are many factors and we know little about your requirements (size of org, technology stack, management systems, the scope of implementation). Our goal was to consolidate APM and infra monitor...

Datadog vs ELK: which one is good in terms of performance, cost and efficiency?

With Datadog, we have near-live visibility across our entire platform. We have seen APM metrics impacted several times lately using the dashboards we have created with Datadog; they are very good c...

Which would you choose - Datadog or Dynatrace?

Our organization ran comparison tests to determine whether the Datadog or Dynatrace network monitoring software was the better fit for us. We decided to go with Dynatrace. Dynatrace offers network ...

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Product Reports

Application Performance Monitoring (APM) and Observability

November 2025

Download Chronosphere product report

Download Datadog product report

December 2025

Overview

Chronosphere provides a robust platform for managing and monitoring cloud-native applications with features like real-time observability, incident management, and capacity planning. It offers scalable, detailed observability across complex systems, an intuitive interface, and cost-efficient resource management. Users report enhanced productivity, improved collaboration, and better decision-making, bolstering operational capabilities and organizational growth.

Chronosphere

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?

Sharable Dashboards: Facilitate collaboration with customizable, intuitive dashboards.
Extensive Integrations: Seamlessly connects with tools like Slack and AWS to support workflows.
APM and RUM: Provides deep insights into application performance and user interactions.
Real-Time Tools: Enables agile responses to system issues with real-time monitoring.
Unified Tagging and Visualization: Eases management of complex systems with simplified visualization.

What Benefits and ROI Should Users Look For?

Efficient Troubleshooting: Centralized logging speeds up the identification and resolution of issues.
Streamlined Workflows: Integrations with popular tools enhance operational efficiency.
Improved Observability: Comprehensive monitoring improves system reliability and performance.
Resource Optimization: Efficient microservices and container management leads to better cloud resource utilization.
Responsive Alerts: Customizable alerts ensure timely identification of critical issues.

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.

Sample Customers

Information Not Available

Adobe, Samsung, facebook, HP Cloud Services, Electronic Arts, salesforce, Stanford University, CiTRIX, Chef, zendesk, Hearst Magazines, Spotify, mercardo libre, Slashdot, Ziff Davis, PBS, MLS, The Motley Fool, Politico, Barneby's