Datadog Headquarters & Office Locations: Full 2026 Directory

Datadog is headquartered at 620 8th Avenue, 45th Floor, New York, NY 10018 — a Midtown Manhattan address the company has called home since its founding in 2010. Beyond its New York City HQ, Datadog operates offices across more than 20 locations globally, spanning North America, Europe, and Asia-Pacific, making it one of the most geographically distributed cloud monitoring vendors in the market.

Where is Datadog headquartered?

Datadog is headquartered in New York City, New York. The company's registered global HQ is at 620 8th Avenue, 45th Floor, New York, NY 10018, in the heart of Midtown Manhattan. This has been Datadog's primary address since its early growth years, and it remained the company's base through its September 2019 IPO on the Nasdaq.

New York was a deliberate choice for co-founders Olivier Pomel and Alexis Lê-Quôc, who launched Datadog in 2010 to solve the infrastructure monitoring challenges they experienced firsthand at previous engineering roles. The NYC location gave them access to enterprise sales talent and proximity to the financial services and media companies that became early Datadog customers.

Today the New York headquarters houses executive leadership, go-to-market leadership, and a significant portion of the company's global sales and marketing teams. Engineering is distributed more broadly, with Boston and Paris serving as major engineering centres.

What are Datadog's office locations worldwide?

Datadog's global footprint reflects its growth from a New York startup to a publicly traded cloud monitoring platform with customers in over 150 countries. The company's offices cluster around three regions: North America, Europe, and Asia-Pacific.

North America offices

Europe offices

Asia-Pacific offices

This distribution is consistent with Datadog's revenue split. According to Datadog's annual report filings, the United States represents the largest share of revenue, followed by EMEA and APAC — a pattern that maps directly onto where the company has concentrated its office infrastructure.

How big is Datadog as a company?

Datadog has grown into one of the largest cloud-native software companies in the world. As of fiscal year 2024, the company reported over $2.68 billion in annual revenue, representing roughly 26% year-over-year growth — a figure that underscores the scale of its installed customer base.

The company employs more than 6,500 people globally, with headcount distributed across its network of offices and a significant remote-first engineering workforce. Datadog's customer count exceeded 29,000 as of late 2024, with over 3,500 customers spending more than $100,000 annually — its highest-value customer cohort and the segment that drives the majority of its ARR.

"The scalability of Datadog's platform across observability, security, and AI means that once a company standardises on it, switching costs are high — they're deeply embedded in the DevOps workflow."

— Analyst note, Barchart DDOG coverage, 2024

That embedded position is exactly what makes Datadog's customer base interesting from a competitive standpoint. Companies that have standardised on Datadog are active, paying users of cloud observability tooling — which means they have the budget, the technical maturity, and the established need that competitors like Dynatrace, New Relic, Grafana, and Honeycomb are actively trying to displace.

Why do sales teams research Datadog office locations?

Understanding where Datadog operates — and, more importantly, where its customers operate — is useful context for SDRs and account executives building targeted outbound lists. Datadog's office concentration in New York, San Francisco, Boston, London, and Dublin reflects where its go-to-market motion is strongest, which correlates with where Datadog's customer density is highest.

For teams selling competing or complementary observability, APM, or DevOps tooling, this geographic data helps prioritise territories. If you're running an outbound sequence targeting companies using Datadog as a monitoring solution, you can filter by geography to match your own rep coverage model before a single email goes out.

According to Salesloft's B2B sales benchmark data, targeted outreach campaigns — where reps contact prospects with confirmed tool or vendor context — achieve reply rates two to three times higher than generic lists. That's the difference between a 2% reply rate and a 6–8% reply rate on the same volume of outreach.

The most practical way to build that kind of list at scale is to start with a tool that identifies companies actively using a specific vendor. Stealery lets you search by competitor name — including Datadog — and surfaces companies confirmed to be using it, filterable by size, location, and hiring signals. What would take days of manual research across job boards and technographic databases takes a few minutes.

What is Datadog's history and founding story?

Datadog was founded in 2010 by Olivier Pomel and Alexis Lê-Quôc, two engineers who met while working at Wireless Generation (later acquired by News Corp). Both had experienced the pain of monitoring complex, distributed infrastructure firsthand — at the time, the tooling available was fragmented, expensive, and designed for on-premise architectures that were rapidly being replaced by cloud infrastructure.

The company launched its SaaS monitoring platform in 2012 and grew quickly on the back of the AWS-era cloud migration wave. By the time companies were moving workloads off on-premise servers and into EC2 instances, Datadog had already built deep integrations with AWS, Azure, and Google Cloud that made it the natural monitoring layer for cloud-native teams.

Datadog went public on September 19, 2019, raising approximately $648 million at a valuation of around $7.8 billion. Its Nasdaq IPO was one of the largest SaaS listings of that year, and the stock (ticker: DDOG) has remained a closely watched benchmark for the cloud software sector.

Key milestones

• 2010: Founded in New York City by Pomel and Lê-Quôc
• 2012: Launched SaaS monitoring platform publicly
• 2016: Crossed $100M ARR milestone
• 2019: IPO on Nasdaq (DDOG) at ~$7.8B valuation
• 2021: Expanded into security monitoring with Cloud SIEM and Application Security
• 2023: Launched AI Observability products targeting LLM monitoring
• 2024: Reported $2.68B in annual revenue, 29,000+ customers

Who are Datadog's main competitors?

Datadog competes across several overlapping categories — infrastructure monitoring, APM (application performance monitoring), log management, security information and event management (SIEM), and, increasingly, AI observability. Its competitive set varies by product line, but the most commonly cited direct competitors include:

• Dynatrace — strongest competition in enterprise APM and full-stack observability
• New Relic — repositioned in 2023 to a consumption-based model targeting cost-conscious engineering teams
• Grafana Labs — open-source-first alternative with strong adoption among infrastructure-heavy teams
• Honeycomb — developer-focused observability, popular with engineering-led organisations
• Splunk (now part of Cisco) — competes primarily in log management and SIEM
• Elastic — open-source observability and search, competes on log analytics
• AWS CloudWatch / Azure Monitor / Google Cloud Operations — native cloud monitoring, often used alongside or instead of Datadog in cloud-native environments

For SDRs at any of these vendors — or at companies selling adjacent tooling — understanding that Datadog's customers are active buyers of cloud observability is the starting point. The next question is which of those customers are showing signals of dissatisfaction, expansion, or vendor review. Hiring signals (job postings that mention specific tools), contract renewal timing, and company growth stage are the most reliable indicators.