Brand Intelligence Graphcompany
Company Overview
About Datadog
Datadog is a cloud-native monitoring and security platform founded in 2010 by Olivier Pomel and Alexis Lê-Quôc, headquartered in New York City. The company went public on Nasdaq (DDOG) in September 2019 and has grown to serve over 29,000 customers as of FY2024, generating $2.68 billion in annual recurring revenue, representing approximately 26% year-over-year growth. Datadog's platform spans infrastructure monitoring, application performance management (APM), log management, security monitoring, and AI observability, positioning it as the unified observability stack for cloud-scale engineering teams.
Business Model & Competitive Advantage
The company's technical moat lies in its unified data platform that ingests metrics, traces, and logs from over 750 integrations across cloud providers, containers, databases, and third-party services. Datadog's agent-based architecture provides low-overhead telemetry collection, while its Notebooks and Dashboards enable collaboration across development and operations teams. The 2023-2025 expansion into LLM Observability—monitoring AI model latency, token costs, and hallucination rates—positions Datadog uniquely as enterprises instrument generative AI workloads at scale.
Competitive Landscape 2025–2026
By 2025-2026, Datadog competes in a consolidating observability market against Dynatrace (DT), Grafana Labs, and Cisco's Splunk (acquired March 2024 for $28B). The CrowdStrike global outage in July 2024 reinforced demand for resilient, multi-vendor monitoring. Datadog's platformization strategy—expanding to 20+ products with cross-sell upsell motions—mirrors Palo Alto Networks' approach, driving net dollar retention consistently above 115%. With AI infrastructure monitoring becoming a critical workload, Datadog is positioned to capture spend as enterprises scale GPU clusters and LLM inference pipelines in 2025-2026.
The Datadog Story
Founders
Recent Activity
View all →## What's Changed * chore(deps): bump `rustls` to 0.23.45 by @lucaspimentel in https://github.com/DataDog/datadog-lambda-extension/pull/1376 * test(bottlecap): fix clock race in increment metric tests by @lucaspimentel in https://github.com/DataDog/datadog-lambda-extension/pull/1368 * fix(deps): vuln protobufjs (patch → 7.6.6) [integration-tests/lambda/otlp-node/package.json] by @gh-worker-campaigns-3e9aa4[bot] in https://github.com/DataDog/datadog-lambda-extension/pull/1372 * Revert "chore(deps): bump `rustls` to 0.23.45" (#1376) by @lucaspimentel in https://github.com/DataDog/datadog-lambda-extension/pull/1389 * [SVLS-9800] fix(config): Support AWS Secrets Manager ARNs for dual-shipping additional endpoints by @shreyamalpani in https://github.com/DataDog/datadog-lambda-extension/pull/1391 * [SVLS-9767] build: embed the dependency tree in the binary with `cargo auditable` by @lym953 in https://github.com/DataDog/datadog-lambda-extension/pull/1377 * fix(stats): retry only retriable tra
# Agent ### Prelude Released on: 2026-10-02 - Please refer to the [7.84.1 tag on integrations-core](https://github.com/DataDog/integrations-core/blob/master/AGENT_CHANGELOG.md#datadog-agent-version-7841) for the list of changes on the Core Checks ### Security Notes - Update `golang.org/x/crypto` to v0.56.0. # Datadog Cluster Agent ### Prelude Released on: 2026-10-02 Pinned to datadog-agent v7.84.1: [CHANGELOG](https://github.com/DataDog/datadog-agent/blob/main/CHANGELOG.rst#7841).
Learn how to monitor the performance, data quality, and costs of your Databricks analytics and AI/ML workloads with Datadog.
Learn how to collect Databricks and Spark telemetry with system tables, the Databricks and Spark UIs, job notifications, and the Databricks REST API.
Learn about key metrics for monitoring the health, performance, and costs of Databricks data engineering, analytics, and Model Serving workloads.
Restoring servers isn’t the same as recovering the business. Plan ransomware recovery and use AI-assisted investigation to detect attacks sooner.
## What's Changed * feat(otel-thread-ctx): add autoclean feature to avoid leaks (v43 backport) by @yannham in https://github.com/DataDog/libdatadog/pull/2597 **Full Changelog**: https://github.com/DataDog/libdatadog/compare/v43.0.1...v43.0.2
Learn how to monitor warehouse data quality at rest, detect issues that happen even when pipelines succeed, and trace issues to their source.
Datadog Code Security now supports Supply Chain Firewall, adding central management with allowlists, blocklists, and retroactive scanning of installed packages.
Learn how Datadog built Distributed DataFusion to scale interactive Apache DataFusion queries across multiple machines.
### Features - **AI Guard:** Support HTTPS_PROXY for evaluation requests [#10543](https://github.com/DataDog/dd-trace-js/pull/10543) - **AppSec / AI Guard:** Support anthropic stream response [#10350](https://github.com/DataDog/dd-trace-js/pull/10350) - **General:** Add OTLP adoption markers to trace payloads [#10482](https://github.com/DataDog/dd-trace-js/pull/10482) - **LLM Observability:** Emit gen_ai.* APM tags when LLM Observability is disabled [#10437](https://github.com/DataDog/dd-trace-js/pull/10437) - **Test Optimization:** Make failure media uploads opt-out [#10538](https://github.com/DataDog/dd-trace-js/pull/10538) ### Fixes - **ci:** Preserve Vitest EFD message serialization [#10541](https://github.com/DataDog/dd-trace-js/pull/10541) - **claude-agent-sdk:** Properly record system prompts [#10574](https://github.com/DataDog/dd-trace-js/pull/10574) - **General:** Balance module-load events when require throws [#10535](https://github.com/DataDog/dd-trace-js/pull/10535) - **LLM
### Features - **AI Guard:** Support HTTPS_PROXY for evaluation requests [#10543](https://github.com/DataDog/dd-trace-js/pull/10543) - **AppSec / AI Guard:** Support anthropic stream response [#10350](https://github.com/DataDog/dd-trace-js/pull/10350) - **General:** Add OTLP adoption markers to trace payloads [#10482](https://github.com/DataDog/dd-trace-js/pull/10482) - **LLM Observability:** Emit gen_ai.* APM tags when LLM Observability is disabled [#10437](https://github.com/DataDog/dd-trace-js/pull/10437) - **Test Optimization:** Make failure media uploads opt-out [#10538](https://github.com/DataDog/dd-trace-js/pull/10538) ### Fixes - **ci:** Preserve Vitest EFD message serialization [#10541](https://github.com/DataDog/dd-trace-js/pull/10541) - **claude-agent-sdk:** Properly record system prompts [#10574](https://github.com/DataDog/dd-trace-js/pull/10574) - **General:** Balance module-load events when require throws [#10535](https://github.com/DataDog/dd-trace-js/pull/10535) - **LLM
Company Timeline
Major milestones in Datadog's journey
Leadership Team
Meet the leaders behind Datadog
Olivier Pomel
Olivier Pomel is Co-Founder and CEO of Datadog, serving in this role since June 2010. He met co-founder Alexis Lê-Quôc as an undergraduate at École Centrale Paris and worked with him for nine years at Wireless Generation before founding Datadog. Under his leadership, Datadog has grown from a startup to a publicly-traded S&P 500 company with over $2.6 billion in annual revenue.
Alexis Lê-Quôc
Alexis Lê-Quôc serves as Co-Founder and Chief Technology Officer, overseeing Datadog's technology vision and product development since 2010. He is responsible for the platform's technical architecture and innovation roadmap, including the development of AI-powered observability capabilities and the time-series foundation model TOTO.
David Obstler
David Obstler has served as Chief Financial Officer since October 2018, bringing more than three decades of operational finance experience. He previously served as CFO of TravelClick and has been instrumental in guiding Datadog through its IPO and subsequent growth as a public company.
Adam Blitzer
Adam Blitzer serves as Chief Operating Officer, overseeing Datadog's global operations, go-to-market strategy, and customer success initiatives. He brings extensive experience scaling high-growth SaaS companies.
Amit Agarwal
Amit Agarwal serves as President of Datadog, working closely with the CEO to drive company strategy, product vision, and market expansion initiatives across global markets.
Ami Vora
Ami Vora brings over 20 years of product experience to her role as Chief Product Officer. She previously served as Chief Product Officer at Faire and has been instrumental in expanding Datadog's product portfolio and accelerating innovation.
Sean Walters
Sean Walters serves as Chief Revenue Officer, leading Datadog's worldwide sales organization and revenue growth strategy. He oversees customer acquisition, expansion, and retention across enterprise and commercial segments.
Sara Varni
Sara Varni serves as Chief Marketing Officer with over 15 years of marketing leadership experience. She previously served as CMO at Attentive and Twilio, bringing deep expertise in developer-focused marketing and brand building.
Kerry Acocella
Kerry Acocella serves as Executive Vice President, General Counsel, and Secretary, overseeing all legal affairs, compliance, corporate governance, and regulatory matters for Datadog globally.
Emilio Escobar
Emilio Escobar serves as Chief Information Security Officer, responsible for protecting Datadog's infrastructure, data, and customer information. He oversees the company's security strategy and ensures platform security meets the highest industry standards.
Key Differentiators
Market Leader
Datadog is recognized as a market leader in the DevOps sector, demonstrating strong industry presence and customer trust.
Enterprise Scale
With $2.68B in revenue, Datadog operates at enterprise scale with proven market validation.
Top 3 Ranked
Ranked #2 in the DevOps category, consistently recognized for excellence.
Frequently Asked Questions
Estimated Visibility Trend (Beta)
Simulated 8-week rolling score
Based on estimated brand signals. Historical tracking coming soon.
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