DDOG

Datadog, Inc.

Next est. report 2026-11-05 · BMO

AI '25: Cloud Platform & Software AI '25: Phase 2 Deployment AI '26: Citizen DevOps AI '26: Data Sovereignty AI Short '26: AI-Obsolete Software Agentic Utilities '26: Deterministic Telemetry Agentic Utilities '26: Governance & Zerotrust Business Services '26: AI Governance, Trust & Compliance Data Owners '25: Cybersecurity & Threat Intelligence Data Owners '25: Enterprise Workflow Data Software '26: Consumption-led Pricing

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Overview

Datadog, Inc. provides a cloud-based platform for real-time monitoring and analytics, helping developers and IT teams ensure smooth and secure operations. Its o

Datadog, Inc. provides a cloud-based platform for real-time monitoring and analytics, helping developers and IT teams ensure smooth and secure operations. Its offerings span infrastructure (43%), application performance (33%), logs (17%), and security (7%). Serving nearly half of the Fortune 500 and over 750 AI customers, Datadog achieved 36% year-over-year revenue growth in Q2 2026.

Search Keywords Brand Product

Datadog platform
Bits AI
Datadog for AI
Real User Monitoring
Log Management
Cloud SIEM
GPU Monitoring
Agent Observability
Data Observability
Infinite Cardinality Metrics
AI Guard
Bits Security Analyst
Bring Your Own Cloud
Network Path
Journey Monitoring
cloud monitoring
observability platforms
AI workloads
cloud security
DevOps automation
AI model training
agentic AI
Zero Trust security
AI governance
digital transformation
cloud migration

Search Keywords Event Phrases

Datadog Q2 2026 earnings
DASH user conference 2026

Search Keywords Policy Regulatory

FedRAMP High certification
HIPAA compliance
PII handling

What They Do (Plain English & Analogies): Datadog acts like a digital 'control tower' for businesses that use cloud-based technology. Imagine a massive airline: Datadog is the dashboard that tells the pilots (engineers) if the engines (servers) are running hot, if the cabin pressure (app performance) is dropping, or if there's a security threat in the cargo hold (logs/security). It collects data from every part of a company's cloud infrastructure and turns it into real-time charts and alerts. This helps IT teams fix problems before customers even notice them. In the age of Artificial Intelligence (AI), it also acts as a 'stethoscope' for AI models, monitoring how much they cost to run and whether they are 'hallucinating' or failing, ensuring they operate smoothly and securely. Datadog's platform helps companies observe, secure, and act on their cloud and AI workloads, automating the process from detecting issues to investigating and fixing them.
Very Brief History: Founded in 2010 by Olivier Pomel and Alexis Lê-Quôc, Datadog initially aimed to break down silos between development and operations teams. It began as an infrastructure monitoring tool and quickly expanded its offerings to include Application Performance Monitoring (APM) in 2017 and Log Management in 2018, becoming a 'three-pillar' observability leader. The company went public in 2019 and has since broadened its platform into Cloud Security, Software Delivery, and Generative AI observability, with multiple product lines exceeding $1 billion in Annual Recurring Revenue (ARR) by 2025. The company acquired Adaptive ML in June 2026 to accelerate its AI research efforts.
"Street Stereotype": Datadog is widely regarded as the 'Gold Standard' and 'Best-of-Breed' platform in the cloud observability space. It is perceived as an execution machine with a relentless research and development engine that consistently releases numerous features each year. Investors often view it as a high-valuation, high-growth 'compounder' that serves as a primary indicator for the health of the broader cloud and AI ecosystem.
Subsidiaries On Linked In*: Seekret — Acquired by Datadog in 2022
CoScreen — Acquired by Datadog in 2022
Hdiv Security — Acquired by Datadog in 2021
Cloudcraft — Acquired by Datadog in 2021
Adaptive ML — Acquired by Datadog in June 2026; LinkedIn: adaptive-ml
Customer Sectors & Example Clients: Datadog serves a wide range of sectors including Technology, Financial Services, E-commerce, Healthcare, and Retail. They count nearly half of the Fortune 500 as customers. Specific clients mentioned in the recent earnings include a Fortune 10 company expanding its e-commerce business, two neuro labs rapidly scaling AI model training workloads, a South American bank consolidating its monitoring stack, a Fortune 100 health insurance company, and one of the world's largest online media companies. Additionally, all 10 of the top 10 AI leaders are Datadog customers, and this includes hyperscalers using Datadog for in-house AI labs.
New Customers / Segments They'Re Targeting: Datadog is actively targeting and seeing rapid growth from AI-native customers, including neuro labs and hyperscalers for their in-house AI labs, specifically for monitoring AI model training workloads and GPU fleets. They are also expanding their go-to-market approach to focus on the world's largest companies, winning opportunities in complex environments. Following their FedRAMP High certification, Datadog is investing in the buildup of federal and government sales, targeting U.S. federal agencies and public sector customers globally.
Supply Chain And Sourcing Geographies: Datadog runs most of its workloads on cloud infrastructure, meaning related costs are primarily reflected in operating expenses rather than capital expenditures. The company does not explicitly detail a physical supply chain or specific sourcing geographies for hardware or components in the provided information.
Sales Geographies And Expansion Plans: Datadog sells its products across North America and internationally. The company is performing well in all regions, with particular strength in the Americas, especially in the U.S. due to AI activity, and in LatAm. They are expanding their global presence, including the launch of a new data center in the U.K. to serve British customers, particularly as cloud adoption accelerates in regulated industries. Datadog is also expanding go-to-market teams and channel partnerships for public sector customers, both in the U.S. and internationally, following their FedRAMP High certification.
How Key Themes May Help/Hurt: The buildout of 'Agentic Utilities '26: Governance & Zerotrust' strongly benefits Datadog. As autonomous AI agents proliferate, there's a critical need for new security and observability solutions to manage agent behavior, control costs, and prevent data leaks. Datadog's platform, with its integrated observability and security products like AI Guard and Bits Security Analyst, is ideally positioned to provide this 'Agentic Governance.' The Zero Trust architecture, which continuously verifies every agent request, is structurally compatible with Datadog's real-time data collection and enforcement capabilities. Datadog becomes crucial for precise metering of agent usage, cost control, and early detection of anomalies or compromises, which are all central to the 'Governance & Zerotrust' theme. The increasing volume of non-human (agent-generated) API calls and observability data directly translates into higher revenue for Datadog's usage-based model. The company's ability to extend Bits Security Analyst to run on non-Datadog SIEMs further expands its reach within this theme.

3 Main Long-Term Bull Details

Dominant Observability Layer for the AI Economy: Datadog is solidifying its position as the essential 'mission control' for the agentic AI era, with AI-native customers rapidly growing and over 750 AI customers using Datadog to monitor and improve their tech stacks. New products like GPU monitoring, Agent Observability, and AI Guard are capturing high-margin revenue as AI agents move into production and training workloads, including landing hyperscalers for GPU monitoring.
Accelerating Platform Consolidation and Multi-Product Adoption: The company continues to win massive consolidation deals, displacing fragmented open-source and legacy tools with its unified platform. This strategy drives strong multi-product adoption, with 58% of customers now using 4 or more products (up from 52% a year ago), 37% using 6 or more (up from 29%), and 13% using 10 or more (up from 7%), highlighting the mission-critical nature of Datadog's platform and leading to robust net retention.
Broad-Based Core Business Re-acceleration: Beyond AI, Datadog's non-AI customer revenue growth accelerated again this quarter to the high 20s percent year-over-year, up from the mid-20s last quarter and 18% in the year ago quarter. This broad-based strength, combined with low churn (gross revenue retention in the mid- to high 90s), demonstrates the underlying health and expansion potential of Datadog's core business, driven by continued cloud migration and digital transformation.

3 Main Long-Term Bear Details

Usage-Based Volatility and Cost Optimization: Datadog's revenue model, which charges based on data volume, exposes it to potential volatility if customers engage in aggressive cost optimization or if there's a slowdown in overall cloud usage. While AI currently drives increased data, a shift to more efficient inference models or customer-built sophisticated homegrown observability scripts could impact revenue, as evidenced by a usage reduction from their largest customer.
Intense Competitive Pressure: The observability market remains highly competitive, with legacy incumbents and hyperscalers integrating AI-driven features into their own monitoring tools. If open-source alternatives or hyperscaler-native tools improve their agentic capabilities to be 'good enough,' Datadog may face pressure to increase R&D and sales spending, potentially compressing operating margins.
Monetization Uncertainty of New AI Products: While Datadog is aggressively building new AI products like Bits AI and Datadog for AI, their long-term monetization and ability to drive material per-seat or usage-based revenue are still in early stages. If these innovations fail to translate into significant, sustained revenue streams, the stock's AI-driven upside may be capped, despite early positive feedback.

Competitors And Differentiation: Datadog competes with both legacy incumbents and hyperscalers, as well as open-source solutions. Their differentiation lies in their integrated platform strategy, which combines and automates infrastructure oversight, application performance tracking, log management, and security surveillance to deliver live, end-to-end visibility. They are actively displacing fragmented legacy monitoring stacks and multiple commercial and internal tools by offering a unified platform. Datadog's AI-driven capabilities, such as Bits AI for automating the DevOps and development loops, and Datadog for AI to observe and secure the AI stack, are key differentiators. The company's ability to handle complex, heterogeneous environments, including diverse silicon and cloud providers, also sets it apart.
Recent Performance & What The Market'S Focused On: Datadog delivered a strong Q2 2026, with revenue reaching $1.12 billion, an increase of 36% year-over-year and above the high end of their guidance range. Revenue growth accelerated across both AI-native customer cohorts and non-AI customers, with non-AI customer revenue accelerating to the high 20s percent year-over-year. The company ended Q2 with about 33,400 customers and approximately 4,720 customers with an ARR of $100,000 or more, generating about 91% of their ARR. Free cash flow was $279 million, with a 25% margin. The market is focused on the continued acceleration of both AI and non-AI customer growth, the strong multi-product adoption, and the impact of AI as a new growth driver. However, management also flagged a usage reduction from their largest customer, which was incorporated into their Q3 and full fiscal year 2026 guidance, leading to some market scrutiny regarding large customer concentration and usage variability. The market is also tracking the monetization of new AI products like Bits AI and Datadog for AI, and the company's expansion into new markets like federal government.

Revenue Segments And Estimated Mix: Infrastructure Monitoring — Mix: ~43% of revenue previously; Source: Q4 2025 earnings summary
Application Performance Monitoring (APM) & Digital Experience Monitoring (DEM) — Mix: ~33% of revenue previously; Source: Q4 2025 earnings summary; Trend: Real User Monitoring (RUM) now exceeds $200 million in ARR and accelerated to over 50% growth year-over-year in Q2 2026.
Log Management — Mix: ~17% of revenue previously; Source: Q4 2025 earnings summary
Cloud Security (SIEM) — Mix: ~7% of revenue previously; Source: Overview table
Data Observability — Mix: n/m; Source: Transcript mentions as newer product
Cloud Service Management (On-call) — Mix: n/m; Source: Transcript mentions as newer product
Product Brands: Infrastructure Monitoring
Application Performance Monitoring (APM)
Log Management
Cloud Security (SIEM)
Real User Monitoring (RUM)
Synthetics
Product Analytics
Network Performance Monitoring
Network Device Monitoring
Serverless Monitoring
Cloud Cost Management
CI Visibility
Observability Pipelines
Universal Service Monitoring
Data Streams Monitoring
Database Monitoring
Data Jobs Monitoring
Continuous Profiler
Dynamic Instrumentation
Sensitive Data Scanner
Audit Trail
Cloud Security Posture Management
Workload Protection
Cloud Infrastructure Entitlement Management
Vulnerability Management
Compliance
App and API Protection
Software Composition Analysis
Code Security
Static Code Analysis (SAST)
Runtime Code Analysis (IAST)
IaC Security
Cloud SIEM
Browser Real User Monitoring
Mobile Real User Monitoring
Experiments
Session Replay
Synthetic Monitoring
Mobile App Testing
Continuous Testing
Error Tracking
BYOC Log Management
Internal Developer Portal
CI Visibility Test Optimization
Feature Flags
Code Coverage
AI Impact Service Level Objectives
Incident Response
Event Management
Case Management
Bits AI Agents
Bits Code
Bits Investigation
Bits Security Analyst
Bits Agent Builder
Bits Chat
MCP Server
Pup CLI Agent Directory
Metrics Watchdog
Agent Observability AI Integrations
Workflow Automation App Builder
CoScreen Teams Dashboards
Notebooks Mobile App Fleet Automation
Governance Console Access Control
OpenTelemetry Alerts integrations
IDE Plugins
API Marketplace
Security Labs Research Open Source Projects
Storage Management
GPU Monitoring
DORA Metrics
Secret Scanning
LLM Observability
Watchdog Anomaly detection
Bit Assistant
Flex Logs
Bits Release
Bits Testing
Datadog for AI
Bits Data Analysis
Agent Console
Network Path
Network Configuration Management
Bits Database Optimizer
Federating Logs
Bring Your Own Cloud (BYOC) for Metrics
Bring Your Own Cloud (BYOC) for Traces
Journey Monitoring
Infinite Cardinality Metrics
AI Guard Agent Discovery
AI Guard for Custom Agents
AI Guard for Coding Agents
Runtime Prioritization Engine
Toto (time series model)

Bull / Bear Details

Datadog's Q2 2026 revenue accelerated to 36% with non-AI customer growth reaching high 20s%, reinforcing its mission-critical role in the agentic AI era. The pl

Thesis

Datadog's Q2 2026 revenue accelerated to 36% with non-AI customer growth reaching high 20s%, reinforcing its mission-critical role in the agentic AI era. The platform continues to dominate AI observability, expanding into model training and securing AI stacks with new Bits AI and AI Guard products. Despite a large customer usage reduction impacting near-term guidance, robust multi-product adoption and strong new logo acquisition underscore a compelling bull case as of 2026-08-15.

Bull case

Datadog's core business is re-accelerating, with Q2 2026 revenue growth hitting 36% year-over-year and non-AI customer revenue accelerating to the high 20s%. This broad-based strength is further bolstered by record new logo dollar bookings, which more than doubled year-over-year, and new customers contributing 30% to the overall revenue growth, demonstrating strong market demand and successful go-to-market execution.
Datadog is solidifying its dominant position as the observability layer for the AI economy. It now serves over 750 AI customers, including all top 10 AI leaders, and is capturing the nascent AI model training market with new 7-figure deals for GPU monitoring. The explosion of agentic activity, evidenced by MCP tool calls quadrupling QoQ and growing 22x YoY, positions Datadog for high-margin revenue capture.
Datadog's platform strategy continues to drive strong multi-product adoption and consolidation, with 58% of customers now using four or more products, and 13% using ten or more. The launch of over 100 new products and features, including Bits AI for automated DevOps and AI Guard for security, enhances platform stickiness. Large consolidation deals, like a multi-year $30M+ TCV win displacing four tools, validate its comprehensive value proposition.

Bear case

Management's FY2026 revenue guidance of 30% year-over-year, while an improvement, still reflects conservatism due to a significant usage reduction from its largest customer starting in Q3. This highlights ongoing concentration risk and potential volatility in large customer consumption, where optimization or shifts by key accounts can materially impact Datadog's growth trajectory and premium valuation, despite strong performance elsewhere.
Competitive pressures persist, and the high cost of Datadog's comprehensive platform remains a friction point, as evidenced by CFO complaints about bills. While new features like Infinite Cardinality Metrics aim to address cost predictability, the slight dip in gross margin to 79.6% suggests ongoing investment or pricing dynamics. If open-source alternatives or hyperscaler-native tools improve capabilities, Datadog may face increased pressure to maintain its lead.
The rapid evolution of the agentic AI era introduces inherent unpredictability regarding long-term observability consumption patterns. While Datadog's usage-based model benefits from increased data volume, customers are actively seeking ways to "rein in their AI costs." This suggests a potential for customers to leverage AI agents or new tools to optimize observability spend in unforeseen ways, or for new, disruptive agent-native observability paradigms to emerge, potentially altering Datadog's competitive landscape.

Bull / Bear Case

Bear Case: Management's FY2026 revenue guidance of 30% year-over-year, while an improvement, reflects conservatism due to a significant usage reduction from its largest customer starting in Q3. This highlights ongoing concentration risk and potential volatility in large customer consumption, which can materially impact growth and premium valuation. Competitive pressures persist, and the high cost of Datadog's platform remains a friction point, as evidenced by CFO complaints and a slight dip in gross margin to 79.6%. If open-source alternatives or hyperscaler-native tools improve capabilities, Datadog may face increased pressure. The rapid evolution of the agentic AI era introduces unpredictability, with customers actively seeking to "rein in their AI costs," potentially leading to optimized observability spend or the emergence of disruptive agent-native observability paradigms.
Bull Case: Datadog's core business is re-accelerating, with Q2 2026 revenue growth at 36% year-over-year and non-AI customer revenue accelerating to the high 20s%. This broad-based strength is supported by record new logo dollar bookings, which more than doubled year-over-year, and new customers contributing 30% to overall revenue growth. Datadog is solidifying its dominant position as the observability layer for the AI economy, serving over 750 AI customers, including all top 10 AI leaders. The explosion of agentic activity, with MCP tool calls quadrupling QoQ and growing 22x YoY, positions Datadog for high-margin revenue capture. The platform strategy drives strong multi-product adoption (58% of customers use 4+ products) and consolidation, validated by large deals displacing multiple legacy tools. New products like Bits AI and AI Guard enhance platform stickiness and address evolving AI and security challenges.
More Compelling & Why: Bear. Datadog's premium valuation, with a forward P/S ratio likely in the 15x-18x range, appears stretched given the market's negative reaction to the Q3 guidance, which incorporates a significant usage reduction from its largest customer. This highlights concentration risk and usage-based volatility, even amidst strong underlying business. The strongest bear argument is the potential for continued customer cost optimization and unpredictable AI consumption patterns impacting future revenue growth, despite AI tailwinds. My view would flip to Bull if Datadog consistently beats its derisked guidance, demonstrating resilience against large customer fluctuations and proving the sustained, high-margin monetization of its new AI products.

Key Factors5 rows

Key Factor	Why It Matters	What To Watch	What It Signals	Where/How To Track
New Logo Dollar Bookings and Contribution to Revenue Growth	This metric demonstrates Datadog's continued ability to attract new, high-value enterprise customers and expand its market reach, which is crucial for sustaining overall revenue growth and future expansion.	Track the year-over-year growth in new logo annualized bookings and the reported percentage of year-over-year revenue growth attributed to new customers.	Bullish if new logo annualized bookings continue to show strong double-digit year-over-year growth (e.g., >50% YoY) and new customer contribution to YoY revenue growth remains at 30% or increases. Bearish if new logo annualized bookings growth significantly decelerates (e.g., below 25% YoY) or new customer contribution to YoY revenue growth declines below 25%.	Datadog's quarterly earnings conference calls and investor presentations. The next update would be in early November 2026.
Impact of Largest Customer Usage Reduction on Guidance	This highlights concentration risk and potential volatility from large customer consumption, which could impact future guidance and the overall growth trajectory if the reduction is larger or more prolonged than currently anticipated.	Monitor management commentary on the largest customer's usage trends in subsequent quarters and any revisions to guidance specifically related to this customer's consumption patterns.	Bullish if Datadog's overall revenue guidance for Q3 and FY2026 is raised in subsequent quarters, indicating the business's ability to absorb the largest customer's reduction. Bearish if the largest customer's usage reduction is larger or more prolonged than currently anticipated, leading to further downward revisions in guidance.	Datadog's quarterly earnings conference calls and associated press releases. The next update would be in early November 2026.
Acceleration in Broad-based (Non-AI Native) Revenue Growth	This indicates the underlying health and strength of Datadog's core business, demonstrating successful platform consolidation and reduced reliance on the potentially more volatile AI-native customer segment. Sustained acceleration de-risks the investment case.	Monitor Datadog's reported year-over-year revenue growth rate for its non-AI customers in future earnings calls.	Bullish if non-AI customer revenue growth remains in the high 20s% year-over-year or accelerates further in subsequent quarters. Bearish if it decelerates below the mid-20s% year-over-year.	Datadog's quarterly earnings conference calls and associated press releases. The next earnings call would typically be in early November 2026 for Q3 2026 results.
Model Context Protocol (MCP) Tool Call Velocity	This metric directly reflects the adoption and scaling of AI agents leveraging Datadog's platform, indicating its critical role in the emerging agentic AI era and its potential for future revenue growth from AI workloads.	Track the quarter-over-quarter growth rate of 'tool calls' to the Datadog MCP server, as well as the year-over-year growth multiple.	Bullish if MCP tool calls continue to show strong quarter-over-quarter growth (e.g., >50% QoQ) or maintain a high year-over-year growth rate (e.g., >10x YoY). Bearish if the quarter-over-quarter growth rate significantly decelerates (e.g., below 25% QoQ).	Datadog's quarterly earnings conference calls and investor presentations. The next update would be in early November 2026.
Multi-Product Adoption (Customers using 4+ or 6+ products)	Increasing multi-product adoption signifies strong platform stickiness, greater customer value derived from Datadog's offerings, and an expanding share of wallet, which are key drivers for higher net revenue retention and long-term ARR growth.	Monitor the reported percentage of customers using 4 or more products, 6 or more products, and 10 or more products year-over-year.	Bullish if the percentage of customers using 4+ products continues to increase year-over-year (e.g., above 58%) and 6+ products (e.g., above 37%). Bearish if these percentages stagnate or decline year-over-year.	Datadog's quarterly earnings conference calls and investor presentations. The next update would be in early November 2026.

Key Reported Metrics, Reratings Triggers & Results3 rows

Rapid growth in MCP tool calls signifies increasing adoption and integration of AI agents into developer workflows, positioning Datadog to capture high-margin r

Upcoming print · 2026-11-05

Key reported metrics
Metric	Last period	Why it matters
Model Context Protocol (MCP) Tool Call Velocity	>2100%	Rapid growth in MCP tool calls signifies increasing adoption and integration of AI agents into developer workflows, positioning Datadog to capture high-margin revenue from the expanding AI economy.
Broad-based (Non-AI Native) Revenue Growth	high 20s percent year-over-year	This metric indicates the health and acceleration of Datadog's core enterprise business, demonstrating successful platform consolidation and reduced reliance on the volatile AI-native cohort.
Total Revenue Growth	$1.12 billion (36% year-over-year growth); Full-year 2026 guidance raised to $4.45 billion to $4.47 billion (30% year-over-year growth)	Sustaining strong total revenue growth is crucial for Datadog's premium valuation and signals continued market leadership and demand for its comprehensive observability platform.

Last reported · 2026-08-06

Key reported metrics			Rerating thresholds			Earnings results
Metric	Last period	Why it matters	What's needed for rerating	Rerating context	Earnings date	Actual reported	Hit target?	Notes
Customers with ARR of $100,000 or more (Count Growth)	21%	Growth in this customer segment is a key indicator of Datadog's ability to land and expand with larger, higher-value customers, which are crucial for long-term ARR growth and platform adoption, especially in the AI era.	An acceleration to 25% or more year-over-year growth.	This metric is crucial as it directly reflects Datadog's ability to land and expand with high-value customers, which drive 90% of its ARR. An acceleration would validate its 'land and expand' strategy and AI adoption, justifying its premium valuation and reinforcing its competitive position.	2026-08-06	4,720 customers, 22.6% year-over-year growth	No	The company reported 4,720 customers with an ARR of $100,000 or more, up from 3,850 a year ago, which translates to approximately 22.6% year-over-year growth. While this represents solid growth, it did not meet the rerating trigger of 25% or more year-over-year growth.
Broad-based (Non-AI Native) Revenue Growth	mid-20%	This metric indicates the health and acceleration of Datadog's core enterprise and SMB business, demonstrating successful platform consolidation and reduced reliance on the volatile AI-native cohort.	The Broad-based (Non-AI Native) Revenue Growth needs to accelerate to at least 28%+ year-over-year, representing a clear re-acceleration beyond the mid-20% reported in Q1 2026 and the 23% in Q4 2025.	This metric indicates the health and acceleration of Datadog's core enterprise business, demonstrating successful platform consolidation and reduced reliance on the volatile AI-native cohort. Sustained acceleration in non-AI revenue would de-risk the investment case, justify premium valuation multiples, and contribute to the overall 30%+ total revenue growth needed for a positive rerating.	2026-08-06	high 20s percent year-over-year	Yes	Datadog reported that revenue growth for its non-AI customers accelerated to the high 20s percent year-over-year, up from the mid-20s percent last quarter. This acceleration was highlighted by management as a key indicator of the underlying strength and health of the core business, demonstrating successful platform consolidation and reduced reliance on the AI-native cohort.
Total Revenue Growth	32%	As a high-growth category leader, sustaining strong revenue growth is critical for Datadog's premium valuation and signals continued market leadership and demand for its platform.	Datadog needs to report Q2 2026 Total Revenue Growth of at least 32% year-over-year, significantly exceeding its own guidance of 29-31% and analyst consensus of approximately 30-31%. Additionally, the company must raise its full-year 2026 revenue guidance to at least 29-30% year-over-year, demonstrating sustained acceleration and robust AI monetization.	Datadog's premium valuation depends on its status as a high-growth category leader. Exceeding revenue growth expectations and raising guidance would validate strong AI-driven demand and platform consolidation, justifying a higher multiple and reinforcing market leadership.	2026-08-06	$1.12 billion (36% year-over-year growth); Full-year 2026 guidance raised to $4.45 billion to $4.47 billion (30% year-over-year growth)	Yes	Datadog exceeded its Q2 2026 total revenue growth target, reporting 36% year-over-year growth, which was above its own guidance and analyst consensus. Additionally, the company raised its full-year 2026 revenue guidance to 30% year-over-year, meeting the rerating threshold. Management noted that this strong performance and guidance raise occurred despite a 'user reduction starting in Q3' from its largest customer, which was 'fully derisked' in the guidance to highlight the overall strength of the business.

Key Questions

Will Datadog's accelerating AI-native customer growth, particularly in AI model training and agentic activity (e.g., MCP tool calls), continue to drive sustaine

Will Datadog's accelerating AI-native customer growth, particularly in AI model training and agentic activity (e.g., MCP tool calls), continue to drive sustained higher revenue growth and solidify its 'Agentic Governance' moat against potential in-house solutions and competitors?

Question 2: Can Datadog continue to accelerate its platform consolidation strategy, leveraging new AI Guard and Bits Security Analyst products, to drive significant ARR expansion and displace legacy observability and security tools across its diverse customer base, especially in the context of Zero Trust for AI workloads?
Question 3: Will the broad-based acceleration in Datadog's non-AI customer revenue and the rapid growth of its AI-native cohort (excluding the largest customer) fully offset the impact of the largest customer's usage reduction, leading to upside beats on its Q3 and FY2026 revenue guidance?

Earnings Transcript Summary3 rows

2026-08-06 · 2026Q2 Earnings Call

3 Things Management Is Most Focused On	Call Takeaway & Tone	Prior Quarter'S Y/Y Growth By Segment	3 Things Analysts Most Pressed On (And Mgmt Responses)	Revenue Segments
3 Things Management Is Most Focused On1. Leveraging AI as a multi-faceted growth driver: Management emphasized AI as a significant tailwind, noting the growth and diversification of AI-native customer cohorts, and the acceleration of non-AI customer cloud and modern technology usage due to AI. They are focused on 'AI for Datadog' (Bits AI products for DevOps and development loops) and 'Datadog for AI' (products to observe, secure, and optimize the AI stack, like GPU Monitoring and AI Guard), as well as groundbreaking AI research. 2. Expanding platform adoption and consolidation: Management highlighted the continued success of their platform strategy, with increasing multi-product adoption (58% of customers use 4+ products, up from 52% a year ago; 37% use 6+ products, up from 29%; 13% use 10+ products, up from 7%) and large consolidation deals displacing multiple legacy tools. 3. Driving broad-based revenue acceleration and customer growth: Olivier Pomel and David Obstler both noted the acceleration of revenue growth across their customer base, including non-AI customers (high 20s% y/y, up from mid-20s% last quarter and 18% a year ago), and robust usage growth from existing and new customers. They also highlighted strong new logo dollar bookings, particularly in enterprise, and faster ramping new logos.	Call Takeaway & ToneThe overall tone of the call was highly positive and confident, despite acknowledging a usage reduction from their largest customer. Management emphasized strong execution, broad-based revenue acceleration (including non-AI customers), and the significant tailwind from AI adoption. They highlighted the success of their integrated platform strategy, increasing multi-product adoption, and continuous innovation in AI-powered observability and security solutions. The takeaway is that Datadog is well-positioned to capitalize on the secular trends of cloud migration, digital transformation, and the emerging AI era, with robust underlying business momentum offsetting specific customer fluctuations.	Prior Quarter'S Y/Y Growth By SegmentIn Q1 2026, total revenue grew 32% year-over-year. Non-AI customer revenue growth accelerated to the mid-20s percent year-over-year. The year-over-year growth rate for Real User Monitoring (RUM) was not explicitly provided for Q1 2026.	3 Things Analysts Most Pressed On (And Mgmt Responses)1. Largest customer usage reduction and its impact on guidance: Sanjit Singh asked for more details on the new contract, its duration, and whether the lower usage was due to lower unit price or churn/downsell. Management (Olivier Pomel and David Obstler) stated they do not comment on specific customers but chose to 'fully derisk the guidance for the rest of the year' with respect to this customer to avoid overshadowing the acceleration seen elsewhere in the business. They reiterated their consistent guidance methodology, factoring in commitment and usage variability. 2. The impact of AI inference on observability needs: Raimo Lenschow inquired about the increased observability required as inference becomes a larger part of AI workloads, specifically mentioning vector databases, guardrails, and container monitoring. Olivier Pomel responded that there's an opportunity at 'every layer of the stack in inference,' from infrastructure (GPUs) to agent outcomes, and all layers in between. He noted growing adoption of existing products like GPU monitoring and agent monitoring, and that the market is evolving, with customer concerns shifting from correctness to cost optimization. 3. CFO concerns about Datadog bills and the role of Infinite Cardinality Metrics: Gabriela Borges highlighted that while engineers love the innovation, CFOs sometimes complain about Datadog bills, asking about the evolution of CFO conversations and if Infinite Cardinality is addressing cost questions. Olivier Pomel explained that customers buy software to make or save money, and Datadog helps save money on building, running operations, or AI agents. He confirmed that Infinite Cardinality Metrics address a long-standing customer frustration regarding unpredictable bills due to high cardinality data, which is particularly relevant as customers build more AI applications and send more tags.	Revenue SegmentsOverall revenue increased 36% year-over-year. Revenue growth for non-AI customers accelerated to the high 20s percent year-over-year. Real User Monitoring (RUM) ARR growth accelerated to over 50% year-over-year.

2026-05-07 · 2026Q1 Earnings Call

3 Things Management Is Most Focused On	Call Takeaway & Tone	Prior Quarter'S Y/Y Growth By Segment	3 Things Analysts Most Pressed On (And Mgmt Responses)	Revenue Segments
3 Things Management Is Most Focused On1. Accelerating revenue growth and strong Q1 performance: Management highlighted the strong start to 2026 with 32% year-over-year revenue growth, accelerating from 29% last quarter, driven by broad-based acceleration across both AI and non-AI customers. 2. Platform strategy and product adoption: They emphasized the continued resonance of their platform strategy, with increasing multi-product adoption (56% of customers use 4+ products, up from 51% a year ago) and significant new product launches, particularly in AI (AI for Datadog, Datadog for AI, GPU monitoring, Bits AI security agent, Bits Assistant, MCP server). 3. Capitalizing on secular growth drivers: Management reiterated that digital transformation and cloud migration remain long-term secular growth drivers, with AI now identified as an additional, significant secular growth driver, positioning Datadog to help customers with AI adoption journeys.	Call Takeaway & ToneThe overall tone of the call was highly positive and confident. Datadog reported a very strong start to 2026, with revenue growth accelerating to 32% year-over-year, driven by broad-based strength across both AI-native and non-AI customers. Management emphasized the success of their platform strategy, leading to increased multi-product adoption and significant new product innovations, particularly in AI observability and security. The company is successfully displacing legacy vendors and expanding its market opportunity by addressing the complexities of cloud migration, digital transformation, and the emerging AI landscape, including new opportunities in AI model training. Management expressed strong confidence in their Q2 outlook, supported by record ARR additions and diversified customer growth.	Prior Quarter'S Y/Y Growth By SegmentIn the prior quarter (2025Q4), total revenue grew 29% year-over-year. Broad-based (non-AI native) usage grew 23% year-over-year.	3 Things Analysts Most Pressed On (And Mgmt Responses)1. Growth in code production due to AI code generators and its impact on Datadog: Analysts questioned how the exponential growth in code production from AI generators like GitHub Copilot affects Datadog's activity. Olivier Pomel responded that they "definitely think and see that there's many more applications being created" and "way more complexity in production," driving an "inflection point" in customer consumption for Datadog. 2. Increasing heterogeneity of silicon (custom chips like Trinium, Graviton, TPUs) and its tailwinds for Datadog: Analysts asked if the proliferation of custom silicon makes monitoring more difficult for traditional tools but provides tailwinds for Datadog. Olivier Pomel affirmed this, stating that "the more heterogeneous, the more you need someone else to make sense of everything for you and title together." He also noted that AI model training, previously a niche, is now becoming a viable market for Datadog, attracting hyperscalers. 3. The future of observability when agents perform triaging/investigating versus human engineers, and potential new pricing modalities: Analysts inquired about Datadog's vision for how the category evolves with AI agents and if pricing models might change. Olivier Pomel responded that their usage-based business model is well-suited regardless of whether usage comes from humans or agents. He observed both a "stratospheric increase of agent usage" and continued "increase of usage of the web interface by humans," indicating both modalities are growing hand-in-hand.	Revenue SegmentsTotal revenue grew 32% year-over-year. Non-AI customer revenue growth accelerated to mid-20% year-over-year. AI native customer growth continued to significantly outpace the rest of the business. Total ARR now exceeds $4 billion, and quarterly revenue exceeded $1 billion for the first time. 5 products are over $100 million in ARR, and another 3 are between $50 million and $100 million ARR.

2026-02-10 · 2025Q4 Earnings Call

3 Things Management Is Most Focused On	Call Takeaway & Tone	Prior Quarter'S Y/Y Growth By Segment	3 Things Analysts Most Pressed On (And Mgmt Responses)	Revenue Segments
3 Things Management Is Most Focused On1. AI Product Innovation: Executing a dual strategy of 'AI for Datadog' (Bits AI SRE agents to automate root cause analysis) and 'Datadog for AI' (observability for LLM stacks and GPU fleets). 2. Platform Consolidation: Displacing legacy vendors and open-source tools through unified observability, evidenced by 18 deals over $10M TCV this quarter. 3. Scaling Go-to-Market: Expanding sales capacity and geographic reach to maintain productivity while capturing the long-term secular trend of cloud migration.	Call Takeaway & ToneTone: Highly Positive and Confident. Takeaway: Datadog delivered a standout quarter characterized by the re-acceleration of its core non-AI business and massive deal wins within the AI-native cohort. The company is successfully positioning itself as the critical 'mission control' for the agentic AI era, with strong multi-product adoption (9% of customers using 10+ products) and robust free cash flow margins.	Prior Quarter'S Y/Y Growth By SegmentTotal Revenue: 26% y/y; Broad-based (non-AI native) usage: 20% y/y; Core APM: ~31% y/y (estimated based on management's commentary regarding Q4 acceleration).	3 Things Analysts Most Pressed On (And Mgmt Responses)1. Defensibility against Agentic AI: Analysts asked if AI agents could eventually build their own observability. Mgmt responded that AI increases system complexity and data volume, making Datadog's real-time data plane and specialized models more essential for proactive resolution. 2. 2026 Guidance Conservatism: Analysts questioned the 18-20% revenue growth guide for FY26. Mgmt explained they apply conservatism to the usage of their largest customers and maintain a consistent guidance philosophy despite strong current trends. 3. Competition and Build-vs-Buy: Analysts asked about the threat of open-source or in-house solutions. Mgmt argued that DIY is economically irrational for most companies due to high engineering costs and that Datadog provides faster velocity and better ROI.	Revenue SegmentsTotal Revenue: 29% y/y; Broad-based (non-AI native) usage: 23% y/y; Core APM: Mid-30s% y/y; Infrastructure Monitoring: ARR >$1.6B; Log Management: ARR >$1B; APM & DEM: ARR >$1B.

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2026-08-06

About Expanding Eligible Market	About Competition	About The Broader Industry	Where Things Are Headed	Updates On Theme	Broader Themes Emerging	Bullish-Leaning Quotes (Short)	Bearish-Leaning Quotes (Short)	Hiring
About Expanding Eligible MarketDatadog is expanding its market by growing its AI-native customer cohort, increasing multi-product adoption (58% use 4+ products, 13% use 10+ products), and securing large enterprise deals, including a 6-figure Fortune 10 e-commerce deal, 7-figure deals with two neuro labs for AI model training and GPU monitoring, a 7-figure deal with a South American bank for legacy stack consolidation, and a multi-year, $30M+ TCV deal with a major online media company displacing 4 tools and including their largest Bring Your Own Cloud win. All 10 of the top 10 AI leaders are Datadog customers, and AI agentic activity (MCP tool calls) quadrupled quarter-over-quarter. New logo dollar bookings more than doubled year-over-year, with new logos contributing 30% of year-over-year revenue growth. Geographic strength is noted in the Americas and LatAm, and the company is investing in federal and government sales after FedRAMP High certification.	About CompetitionDatadog is successfully displacing multiple commercial and internal tools, including legacy commercial logging tools at petabyte scale, as evidenced by a $30M+ TCV deal with a major online media company. Its HIPAA compliance and PII handling differentiate it in competitive scenarios. Datadog was named a leader in the 2026 Gartner Magic Quadrant for Observability Platforms for the sixth consecutive year. The company also displaces homegrown monitoring solutions at hyperscalers' AI labs and benefits from the complexity of heterogeneous environments.	About The Broader IndustryThe broader industry is characterized by widespread AI adoption across all customer segments, accelerating cloud usage and digital transformation. AI is now an additional secular growth driver, introducing new complexity and observability challenges that Datadog addresses with its 'Datadog for AI' products. The security industry is undergoing a 'complete rebuild' towards AI-driven automation and integrated platforms, moving away from human-in-the-loop processes. The AI ecosystem is diversifying with many providers and the multiplication of open-source models, leading to more in-house AI model training.	Where Things Are HeadedDatadog is focused on leveraging AI as a significant growth driver, both as a tailwind for cloud consumption and by integrating AI into its platform (Bits AI) to deliver more value and greater capabilities, including automating the DevOps loop and development loop. The company is also developing 'Datadog for AI' to observe and secure the end-to-end AI stack. Future plans include accelerating AI research with acquisitions like Adaptive ML to build larger, more ambitious dedicated models. Datadog aims to position itself as the essential platform for customers to innovate and drive value through AI and cloud adoption, with a vision for observability to evolve into proactive fixing and auto-remediation. The company expects Q3 2026 revenue growth of 28-29% and full-year 2026 revenue growth of 30%.	Updates On ThemeGovernance	Broader Themes EmergingThe emergence of an 'agentic era' where AI agents increasingly automate tasks, shifting focus from code writing to validation and monitoring. A fundamental transformation in security, moving towards AI-driven, automated remediation and integrated platforms. The democratization of AI model training, driven by the proliferation of open-source models.	Bullish-Leaning Quotes (Short)Our revenue growth in Q2 has accelerated across our customer base. Revenue was $1.12 billion, an increase of 36% year-over-year and above the high end of our guidance range. Our quarter-over-quarter revenue added of $115 million is a record by a significant margin. new logo annualized bookings more than doubled from a year ago. The portion of our year-over-year revenue growth that relates to new customers was about 30% in Q2, up from 25% in Q1. AI is a tailwind for Datadog today as cloud consumption grows and drives more use of our platform. all 10 of the top 10 AI leaders are Datadog customers. agentic activity with a number of MCP tool calls quadrupling again quarter-over-quarter and growing more than 22x when compared to Q4 2025. if you back out our largest customer from our growth, you get pretty much the same growth rate as the rest of the business has been accelerating very steadily. The business is booming, and we don't want that to overshadow basically the acceleration we see pretty much everywhere else in the business.	Bearish-Leaning Quotes (Short)we signed a 9-figure renewal with a leading AI company... albeit with a user reduction starting in Q3, which we considered in our guidance. Regarding our largest customer, we have seen a usage reduction, which is incorporated in our Q3 and full year 2026 guidance. For the third quarter, we expect our revenue to be in the range of $1.135 billion to $1.145 billion, which represents a 28% to 29% year-over-year growth. For the full fiscal year 2026, we expect revenue to be in the range of $4.45 billion to $4.47 billion, which represents a 30% year-over-year growth. The CFOs love to complain a little bit about their Datadog bills. Our Q2 gross profit was $892 million for gross margin of 79.6%. This compares to a gross margin of 80.2% last quarter and 80.9% in the year ago quarter.	HiringDatadog is continuing to invest in and add to its go-to-market teams to reach more customers worldwide and in relevant segments, indicating ongoing workforce expansion in sales and marketing roles.

2026-05-07

About Expanding Eligible Market	About Competition	About The Broader Industry	Where Things Are Headed	Updates On Theme	Broader Themes Emerging	Bullish-Leaning Quotes (Short)	Bearish-Leaning Quotes (Short)	Hiring
About Expanding Eligible MarketDatadog's total ARR now exceeds $4 billion, and quarterly revenue exceeded $1 billion for the first time. The company has 26 products, with 5 over $100 million in ARR and 18 earlier-stage products believed to have the potential to grow to over $100 million. New product launches include GPU monitoring and Experiments for general availability. Datadog is expanding geographically with a planned data center in the U.K. and has achieved FedRAMP High certification, allowing it to serve U.S. federal agency customers. The company is also expanding product offerings, go-to-market teams, and channel partnerships for public sector customers globally. Datadog is seeing training become a viable market, landing deals with hyperscalers for monitoring training workloads and GPUs. The company is investing in deploying into more geographies and certifications for the public sector, as well as 'bring your own cloud' products to support customers with data residency and sovereignty needs, potentially enabling entry into extremely large-scale workloads that previously would not have considered SaaS offerings.	About CompetitionDatadog continues to see customers consolidating fragmented observability stacks, replacing multiple legacy APM tools, open-source solutions, and cloud monitoring tools to unify data, automate workflows, and save money. Even hyperscalers, known for building in-house, are turning to Datadog to accelerate innovation on hyperscale AI training workloads and replace existing solutions. Olivier Pomel stated that Datadog is outperforming competitors at scale and taking market share due to its platform, product expansion, and successful growth of sales capacity. The increasing heterogeneity of silicon environments (e.g., Amazon Trinium/Graviton, Google TPUs, Microsoft Myosilicon) favors Datadog, as it can make sense of diverse environments and tie them together with the broader infrastructure and applications, which traditional monitoring tools often fail to do. The urgency of AI development efforts is forcing even large companies to prioritize core activities and rely on Datadog for non-core observability, a shift from their historical 'build it themselves' approach.	About The Broader IndustryThe industry is experiencing strong continued cloud migration and greater adoption of Datadog's products, with customers of all kinds accelerating their use of AI. Digital transformation and cloud migration remain long-term secular growth drivers, now augmented by AI as an additional secular growth driver. There is an observed increase in the sheer volume of code being produced due to code generators, leading to more applications and greater complexity in production, which drives activity for Datadog. The increasing heterogeneity of the silicon environment, with custom chips from major cloud providers, is a trend that plays in Datadog's favor as it makes monitoring more complex. Training of AI models, once limited to a few companies, is democratizing and becoming a more viable market category. The industry is entering an 'agentic era' where the focus is shifting from writing code to validating and monitoring it, with massive hyperscaler CapEx leading to 'very, very, very large increases in complexity,' serving as a long-term tailwind for observability. It's becoming harder to predict future trends, as evidenced by the unexpected return to coding in the console for many engineers.	Where Things Are HeadedDatadog believes it is 'still just getting started,' with 18 of its 26 products in earlier life cycles, each having the potential to grow to over $100 million in ARR. The company is pleased with its start to 2026, supporting customers' inflection in AI usage and application development, and leveraging its AI innovations like Bits AI SRE Agent, Bits AI Security Analyst, Bits Assistant, Datadog MCP server, and GPU monitoring. Datadog sees digital transformation, cloud migration, and AI adoption as long-term secular growth drivers. The company aims to help customers of every size and industry transform, innovate, and drive value through AI and cloud adoption. For Q2 2026, Datadog expects revenues between $1.07 billion and $1.08 billion, representing 29% to 31% year-over-year growth, and for fiscal 2026, revenues between $4.3 billion and $4.34 billion, representing 25% to 27% year-over-year growth. The company is ramping up investments in R&D, particularly in the scale of models it trains. Datadog is investing in deploying into more geographies and securing more government certifications, as well as developing 'bring your own cloud' products to support customers with data residency and sovereignty needs. The company's security strategy emphasizes integrated solutions over point solutions to cover the entire security posture.	Updates On ThemeGovernance	Broader Themes EmergingThe emergence of an 'agentic era' where the focus shifts from writing code to validating and monitoring it, and where AI agents are increasingly performing triaging and investigations. This also implies a shift from human-centric UIs to agent-centric API/MCP interactions for troubleshooting.	Bullish-Leaning Quotes (Short)Our teams executed very well and delivered revenue growth of 32% year-over-year, accelerating from 29% last quarter and 25% in the year ago quarter. Revenue was $9.1 billion, an increase of 32% year-over-year and above the high end of our guidance range. Our total ARR now exceeds $4 billion, and our quarterly revenue exceeded $1 billion for the first time. 56% of our customers now use four or more products, up from 51% a year ago. New logo annualized bookings set a new all-time record by a significant margin and more than doubled versus a year ago quarter. Our trailing 12-month net revenue retention percentage was in the low 120%, up from about 120 last quarter. We are outperforming all of our competitors at scale, and we're taking share.	Bearish-Leaning Quotes (Short)For the second quarter, we expect revenues to be in the range of $1.07 billion to $1.08 billion, which represents a 29% to 31% year-over-year growth. For fiscal 2026, we expect revenues to be in the range of $4.3 billion to $4.34 billion, which represents 25% to 27% year-over-year growth. As with last quarter, we are applying a higher degree of conservatism to our largest customer. In Q2, we will be holding our DASH user conference which we estimate to cost about $15 million in which we have reflected in our operating income guidance.	HiringDatadog's Q1 OpEx grew 31% year-over-year, which is an indication of the company's execution of its hiring plans to pursue long-term growth opportunities. The company has been investing in its go-to-market function, including reps and channel partners, for a number of years, investing ahead of certifications like FedRAMP to build pipeline, and plans for more investment in this area.

2026-02-10

About Expanding Eligible Market	About Competition	About The Broader Industry	Where Things Are Headed	Updates On Theme	Broader Themes Emerging	Bullish-Leaning Quotes (Short)	Bearish-Leaning Quotes (Short)
About Expanding Eligible MarketDatadog is aggressively expanding into the security and service management sectors, with Cloud SIEM and 'On-call' (3,000+ customers) gaining traction. The company highlighted a massive untapped opportunity within the Fortune 500, where 48% are customers but the median ARR is still under $500,000. New product launches like Data Observability, Storage Management, and Feature Flags (foundation for AI agentic development) are broadening the platform's reach. The 'Datadog for AI' suite now has over 1,000 customers, with spans sent increasing 10x over the last six months.	About CompetitionManagement stated they are 'pulling away' and taking share from any competitor with scale, specifically noting a consolidation motion replacing legacy vendors in nearly 100 deals worth tens of millions. Olivier Pomel dismissed recent industry M&A as involving 'not particularly winning companies.' The company is successfully displacing legacy SIEM and logging providers, with one Fortune 500 retailer expected to save millions by replacing a legacy logging product with Flex Logs. Even AI-native companies are moving away from homegrown/open-source tools to Datadog to prioritize developer velocity.	About The Broader IndustryThe industry is entering an 'agentic era' where the focus is shifting from writing code to validating and monitoring it. Pomel noted that massive hyperscaler CapEx (projected at $500B+ for the big three) will lead to 'very, very, very large increases in complexity,' which serves as a long-term tailwind for observability. There is a structural shift toward 'in-stream' analysis, as the volume of data from AI agents makes post-hoc analysis insufficient for maintaining system uptime.	Where Things Are HeadedDatadog is moving toward 'preemptive resolution,' where systems auto-diagnose and remediate issues in real-time before outages materialize. The company is heavily betting on the Model Context Protocol (MCP), with their MCP server seeing 11-fold growth in tool calls in Q4. For FY2026, Datadog expects an inflection in AI usage within applications and is guiding for 18-20% revenue growth, which includes a conservative outlook for its largest customer but 20%+ growth for the core business.	Updates On ThemeCloud	Broader Themes EmergingThe emergence of 'Agentic SREs' and the Model Context Protocol (MCP) as a standard for AI agents to interact with production data; a shift from human-centric UIs to agent-centric API/MCP interactions for troubleshooting.	Bullish-Leaning Quotes (Short)"We signed 18 deals over $10 million in TCV this quarter, of which two were over $100 million."; "Revenue growth accelerated with our broad base of customers, excluding the AI natives, to 23%."; "14 of the top 20 AI-native companies are Datadog customers."; "Log management is now over $1 billion in ARR."	Bearish-Leaning Quotes (Short)"For the full fiscal year 2026, we expect revenues... which represents 18% to 20% year-over-year growth."; "The median Datadog ARR for our Fortune 500 customers is still less than half a million dollars."; "RPO duration increased year over year as the mix of multiyear deals increased."

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Date	Comment	Comment Type	Comment Sentiment	Link	Price Reaction
2025-11-06	Datadog delivered a strong Q3 with accelerating security ARR (+mid‑50s%), broader AI-native growth (12% of revenue, more $1M+ customers), and the strongest non‑AI usage expansion in 12 quarters. Core business strength, improving sales productivity, and early Bits AI traction drove a positive stock reaction and increased confidence in sustained growth.	Earnings Transcript	Bullish		+23.40% (vs SPY: +22.83%)
2025-08-12	Datadog CFO David Obstler highlighted strong Q2 growth driven by AI customer adoption, expanding enterprise deals, and security momentum. Q3 focus: continued AI use case expansion, Bits AI monetization, security go-to-market ramp, and managing log spend with Flex/Frozen solutions to drive upsell and retention.	Conference Presentation	Neutral
2025-08-07	Strong Q2 beat with 28% y/y growth and AI-native momentum, but management flagged possible AI cohort volatility; focus on AI products, security expansion, and margin gains kept outlook solid.	Earnings Transcript	Mixed		-4.42% (vs SPY: -4.92%)
2026-02-10	Datadog's Q4 results sparked an 11.7% stock surge as revenue growth re-accelerated to 29% alongside record bookings (+37% y/y). Key takeaways included massive consolidation deals—including two $100 million+ contracts—and rapid adoption of Bits AI and MCP servers. The market's bullish reaction confirms high confidence in Datadog's AI leadership, effectively dismissing conservative FY26 guidance in favor of strong underlying usage and platform expansion momentum.	Earnings Transcript	Bullish	https://investors.datadoghq.com/	+11.68% (vs SPY: +11.97%)
2026-08-06	Datadog reported strong Q2 2026 results, with revenue up 36% year-over-year and exceeding expectations, and raised full-year guidance. However, the stock plunged 17.39% (T+2 days) due to concerns over modest sequential growth projections, a contraction in free cash flow margins, and a flagged usage reduction from a major AI customer. The market's "sell the fact" reaction indicated high expectations were not fully met, despite positive underlying business momentum and AI-driven expansion.	Earnings Transcript	Mixed		-17.39% (vs SPY: -17.81%)