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Logo of Datadog

Datadog

byDatadog
in
4.2
2025
Market Presence: Observability Platforms, Infrastructure Monitoring Tools

Overview

Product Information on Datadog

Updated 13th October 2025

What is Datadog?

Datadog is a software that offers monitoring and analytics capabilities for cloud-scale applications. The software collects metrics, traces, logs, and events from various sources and provides dashboards, alerts, and visualization tools to help users track the performance and health of systems and services. Datadog integrates with cloud infrastructure, containers, databases, and applications, enabling users to correlate data across their technology stack. The software addresses challenges related to dynamic, distributed environments by providing observability and insights that support incident detection, troubleshooting, and optimization of resources and applications. It is designed to facilitate collaboration between development, operations, and security teams in managing application reliability and system performance.

Datadog Pricing

Datadog software uses a subscription-based pricing model structured by product type with options for pay-as-you-go and tiered plans based on usage volume such as number of hosts, logs, traces, or specific monitoring features, allowing users to select plans that fit different monitoring and analytics requirements.

Overall experience with Datadog

Engineer
<50M USD, IT Services
FAVORABLE

“Unified telemetry streamlines incidents, though rising costs demand careful filtering”

4.0
Jul 4, 2026
This text serves as a placeholder and does not reflect the user’s review responses or opinions. This text serves as a placeholder and does not reflect the user’s review responses or opinions. This text serves as a placeholder and does not reflect the user’s review responses or opinions.
Software Developer
<50M USD, Travel and Hospitality
CRITICAL

“Datadog from confusion to clarity at what cost”

3.0
Jul 16, 2026
This text serves as a placeholder and does not reflect the user’s review responses or opinions. This text serves as a placeholder and does not reflect the user’s review responses or opinions. This text serves as a placeholder and does not reflect the user’s review responses or opinions.

Badges

Gartner Peer Insights recognizes vendors who meet or exceed both the market average Overall Experience and the market average User Interest and Adoption score through a Customers’ Choice distinction.
2025
For Market:
Observability Platforms

About Company

Company Description

Updated 25th July 2024

Datadog specializes in providing a comprehensive monitoring platform for cloud applications. It collects data from diverse sources such as servers, containers, databases, and third-party services, aiming to make the stack fully observable. By offering these features, Datadog assists DevOps teams in preventing downtime, addressing performance problems, and ensuring optimal user experience.

Company Details

Updated 26th February 2025
Company type
Public
Year Founded
2010
Head office location
New York, United States
Number of employees
1001 - 5000
Website
http://datadoghq.com

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Key Insights

A Snapshot of What Matters - Based on Validated User Reviews

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Peer Discussions

Datadog Reviews and Ratings

4.2

(15 Ratings)

Rating Distribution

5 Star
33%
4 Star
53%
3 Star
13%
2 Star
0%
1 Star
0%
Why ratings and reviews count differ?
  • Engineer
    <50M USD
    IT Services
    Review Source

    Unified telemetry streamlines incidents, though rising costs demand careful filtering

    4.0
    Jul 4, 2026
    I have been using DataDog for the past 3 years as our primary observability platform, mainly for telemetry ingestion and to collect telemetry data from our microservices and cloud infrastructure. The main reason we chose it was because of the wide range of built-in integrations and we don't have to create any custom agents for most of our tools. Data Enrichment such as data tagging, hosting metadata & service maps really helped our on-call engineers save time while dealing with critical incidents.
  • Engineer
    <50M USD
    IT Services
    Review Source

    Unified telemetry streamlines incidents, though rising costs demand careful filtering

    4.0
    Jul 4, 2026
    I have been using DataDog for the past 3 years as our primary observability platform, mainly for telemetry ingestion and to collect telemetry data from our microservices and cloud infrastructure. The main reason we chose it was because of the wide range of built-in integrations and we don't have to create any custom agents for most of our tools. Data Enrichment such as data tagging, hosting metadata & service maps really helped our on-call engineers save time while dealing with critical incidents.
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  • Market Guide for Telemetry Pipelines (Transitioning to Observability Pipelines)
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Reviewer Insights for: Datadog
Performance of Datadog Across Market Features

Datadog Likes & Dislikes

Like

1. System integration breadth: DataDog has built-in connections for almost every AWS, Kubernetes, and CI/CD tool we use, which saves us a lot of time setting things up 2. Unified Telemetry ingestion: Logs, Metrics and traces all land in one place, so we don't have to piece together data from three separate tools when something goes wrong 3. Dashboard and alerting flexibility: Different teams like platform, app and security can create their own views that fit their needs without causing conflicts

Like

1. System integration breadth: DataDog has built-in connections for almost every AWS, Kubernetes, and CI/CD tool we use, which saves us a lot of time setting things up 2. Unified Telemetry ingestion: Logs, Metrics and traces all land in one place, so we don't have to piece together data from three separate tools when something goes wrong 3. Dashboard and alerting flexibility: Different teams like platform, app and security can create their own views that fit their needs without causing conflicts

Like

1. System integration breadth: DataDog has built-in connections for almost every AWS, Kubernetes, and CI/CD tool we use, which saves us a lot of time setting things up 2. Unified Telemetry ingestion: Logs, Metrics and traces all land in one place, so we don't have to piece together data from three separate tools when something goes wrong 3. Dashboard and alerting flexibility: Different teams like platform, app and security can create their own views that fit their needs without causing conflicts

Dislike

1. Pricing is confusing and there is no customization at different org levels 2. Customer and tech support is not that great with the new AI bot as standard support 3. Some Documentation is outdated and not clear with different tech stacks

Dislike

1. Pricing is confusing and there is no customization at different org levels 2. Customer and tech support is not that great with the new AI bot as standard support 3. Some Documentation is outdated and not clear with different tech stacks

Dislike

1. Pricing is confusing and there is no customization at different org levels 2. Customer and tech support is not that great with the new AI bot as standard support 3. Some Documentation is outdated and not clear with different tech stacks