- Specialization
Data Engineeringand 1 more specialization valuesLess
- Security
- Business
- Software Applications
- Market
- Cross Industry
- Ecosystem
- Not classified
- Customers
Enterprisesand 1 more customers valuesLess
- Small Businesses
More details
- Organization type
- Commercial Company
- Ecosystem
- Not classified
- Business
- Software Applications
- Specialization
- Data Engineering, Security
- Market
- Cross Industry
- Customers
- Enterprises, Small Businesses
- Delivery models
- Hosted Software
- Revenue models
- Subscription, Usage Based
- Listing status
- Not classified
- Latest equity round
- Not classified
- Reported funding amount
- Not classified
About
Datadog builds a cloud-scale monitoring, observability, and security platform that unifies infrastructure metrics, traces, logs, and related telemetry. Its SaaS product serves organizations of all sizes across industries, helping teams monitor entire technology stacks through one integrated platform.
Market
Datadog competes in cloud observability, application performance monitoring, infrastructure monitoring, and cloud security. It positions itself as an AI-powered, unified platform that correlates metrics, logs, traces, security signals, and AI telemetry, differentiating through broad cloud coverage, Kubernetes and OpenTelemetry support, and more than 1,000 integrations rather than separate point tools.
Datadog targets organizations running cloud applications—from cloud-native companies to large enterprises—whose development, IT operations, security, and business teams need shared visibility across their systems. Its stated users include developers, IT operations teams, and business users, and its enterprise traction is substantial: 48% of the Fortune 500 were customers as of December 2025.
At a Glance
Problem
Modern cloud applications generate operational, performance, user, and security data across many systems, leaving development, operations, security, and business teams to piece together incidents from disparate tools. The resulting pain is slower detection and resolution of problems, duplicated tooling and investigation effort, and less efficient use of cloud infrastructure. Datadog frames the economics directly: reducing mean time to detection and resolution helps customers avoid lost revenue and improve customer experience. A representative killer use case is preventing outages—for example, Datadog says it helps the London Stock Exchange Group proactively identify issues and prevent system outages so the exchange runs smoothly.
Product / Service
Datadog sells a cloud-based SaaS platform that integrates and automates infrastructure monitoring, application performance monitoring, log management, user experience monitoring, cloud security, service management, and other capabilities into unified, real-time observability and security for the technology stack. Its integrated data platform combines monitoring and security data, connects with more than 1,000 technologies through out-of-the-box integrations, and supports incident response workflows that incorporate real-time observability data to speed remediation.
Customers buy subscriptions to use the cloud platform, with plans and billing structures that can accommodate committed or usage-based consumption. The benefit is a single operational view instead of multiple siloed systems: teams can detect, investigate, and respond to problems faster, collaborate across functions, secure applications and infrastructure, and understand application and business performance. Datadog has also expanded beyond core observability into cloud security, software delivery, and service management.
Market
Datadog competes in observability platforms and adjacent IT operations, cloud security, software delivery, and service management markets. Its 2025 Form 10-K describes a worldwide monitoring and analytics market and names IBM, Microsoft, SolarWinds, Cisco, New Relic, Dynatrace, and Elastic as competitors across relevant product categories. Datadog states that the combined markets it participates in represent a $187 billion opportunity in 2029, and it was named a Leader in the 2025 Gartner Magic Quadrant for Observability Platforms.
The company is well beyond pre-revenue: it reported 28% year-over-year revenue growth in 2025 and had approximately 32,700 customers in more than 160 countries at year-end. Its customer base included 4,310 customers with at least $100,000 of annual recurring revenue and 603 with at least $1 million, indicating meaningful adoption by larger enterprises as well as broad-market reach.
Founders & Leadership
Funding History
NYC Seed, RRE Ventures
Index Ventures
Index Ventures, RTP Ventures
OpenView Venture Partners
Index Ventures
ICONIQ Capital
Recent News
Traversal added three capabilities to its incident-investigation product: Datadog RUM analysis for measuring real-user impact, read-only Kubernetes cluster inspection, and deeper GitHub repository analysis using temporary checkouts. The company’s changelog dates these additions October 2, 2026.
Datadog announced Journey Monitoring and Bits Testing, new AI capabilities for the user journey. The announcement said the products bring AI to both ends of that journey.
On 2026-08-18, PgDog announced its official entry into the Datadog Partner Network. The announcement said PgDog would bring Datadog’s observability platform to the cloud architectures it designs and manages.
Vertosoft announced a strategic partnership with Datadog to bring Datadog’s cloud-based monitoring and security platform to U.S. government agencies through Vertosoft’s public-sector distribution network. The announcement highlighted Datadog for Government’s FedRAMP High certification and said the collaboration would help agencies adopt modern, secure observability across infrastructure, applications, and hybrid-cloud environments.
CodeRabbit announced a $143 million Series C financing at a $1.5 billion valuation, co-led by Atomico and Smash Capital. The company said it will use the capital for international expansion, research, and product development, while also introducing its Agentic Change Management platform capabilities.
Datadog disclosed a nine-figure renewal with a longtime leading AI customer during its August 6, 2026 second-quarter earnings call. The unnamed customer uses 17 Datadog products, supporting Datadog’s expansion within a major account.
Datadog acquired Adaptive ML, a startup developing a Reinforcement Learning Operations platform. Adaptive ML will join Datadog’s AI lab to build frontier AI infrastructure for observability and security research.
Datadog’s DASH 2026 announcement roundup covered new capabilities including Bits AI, MCP Apps, Agent Observability, and Journey Monitoring.
Active Roles
437Business Model
Datadog generates substantially all of its revenue from subscriptions to its cloud-based platform. Customers can choose monthly, annual, or multi-year commitments, with pricing based on committed usage, delivered usage, or monthly usage; excess usage is billed incrementally.
Products
Customers
Tech Stack
Similar Companies
Competitors
Key Investors
IVP, OpenView, Index Ventures