#1DATADOG Investor Presentation February 2024 DATADOG#2Safe harbor This presentation and the accompanying oral presentation have been prepared by Datadog, Inc. ("Datadog" or the "company") for informational purposes only and not for any other purpose. Nothing contained in this presentation is, or should be construed as, a recommendation, promise or representation by the presenter or Datadog or any officer, director, employee, agent or advisor of Datadog. This presentation does not purport to be all-inclusive or to contain all of the information you may desire. Information provided in this presentation speaks only as of the date hereof, unless otherwise indicated. This presentation and accompanying oral presentation contain "forward-looking" statements, as that term is defined under the federal securities laws, including but not limited to statements regarding Datadog's strategy, product and platform capabilities, the growth in and ability to capitalize on long-term market opportunities including the pace and scope of cloud migration and digital transformation, the potential size of the cloud, observability and cloud security markets, gross margins and operating margins including with respect to sales and marketing, research and development expenses, investments and capital expenditures, net interest and other income, and Datadog's future financial performance, including its guides, outlook and goals on slides "Rapid Revenue Growth," "Financial Outlook," "New Long-Term Margin, Goal" "Capital Allocation Goals" and "Stock-Based Compensation.". These forward-looking statements are based on Datadog's current assumptions, expectations and beliefs and are subject to substantial risks, uncertainties, assumptions and changes in circumstances that may cause Datadog's actual results, performance or achievements to differ materially from those expressed or implied in any forward-looking statement. The risks and uncertainties referred to above include, but are not limited to (1) our recent rapid growth may not be indicative of our future growth; (2) our history of operating losses; (3) our limited operating history; (4) our dependence on existing customers purchasing additional subscriptions and products from us and renewing their subscriptions; (5) our ability to attract new customers; (6) our ability to effectively develop and expand our sales and marketing capabilities; (7) risk of a security breach; (8) risk of interruptions or performance problems associated with our products and platform capabilities; (9) our ability to adapt and respond to rapidly changing technology or customer needs; (10) the competitive markets in which we participate; (11) risks associated with successfully managing our growth and (12) general market, political, economic, and business conditions including concerns about reduced economic growth and associated decreases in information technology spending. These risks and uncertainties are more fully described in our filings with the Securities and Exchange Commission (SEC), including in the section entitled "Risk Factors" in our Quarterly Report on Form 10-Q for the quarter ended September 30, 2023. Additional information will be made available in our Annual Report on Form 10-K for the year ended December 31,, 2023 and other filings and reports that we may file from time to time with the SEC. Moreover, we operate in a very competitive and rapidly changing environment. New risks emerge from time to time. It is not possible for our management to predict all risks, nor can we assess the impact of all factors on our business or the extent to which any factor, or combination of factors, may cause actual results to differ materially from those contained in any forward-looking statements we may make. In light of these risks, uncertainties and assumptions, we cannot guarantee future results, levels of activity, performance, achievements, or events and circumstances reflected in the forward-looking statements will occur. Forward-looking statements represent our beliefs and assumptions only as of the date specified or as of this presentation, as applicable. We disclaim any obligation to update forward-looking statements. DATADOG 2#3Datadog is the observability and security platform for cloud applications DATADOG#4Evolving technology paradigms create rising complexity Diversity of technologies in use Scale in number of computing units Number of technologies and tools Few vendor suites Standardized/On-prem Frequency of release ✓ Once a day Frequency Waterfall Once a year On-demand Lots of open source and SaaS Diverse/Cloud ☑ Number of nodes Time Static ☑ People Physical hardware Cloud instances ✓ Number of people involved Time Agile Siloed Ops Serverless & microservices Containers Dev + Ops Business + Dev + Ops Security + Dev + Ops + Business Time Integrated Time Dynamic DATADOG 4#5A Azure press Route Amazon Amazon Amazon Machine Learning ElastiCache Microsoft Azure Virtual Machine Scale Set ✓ Datadog solves Amazon CodeBuild complexity Google Google Firebas Cloud Datafi mongoDB amazon webservices Health Groups Google SYSLOG T Teams 600' Amazon SES Cloud TPU Google Microsoft Azure App Service Environment Cloud Memorystore for Redis Microsoft Azure Table Storage ALB Azure Stream Analytics Google Cloud Dataproc Microsoft Azure Google Cloud Pub/Su Amazon DynamoDB Amazon DocumentDB Gremlin VictorOps Amazon Google Polly puts Chat Azure Key Vault Microsoft Azure VM Amazon Route 53 TCP Spark Azure My Microsoll Azure Azure Analysis Servic ustomer Inghts DB for MySQL Azure Application Gateway Amazon Google CloudHSM Cloud Firestore SQL Core OS Microsoft Azure SQL Elastic Pool H Amazon API Gateway Azure CosmosDB Google Cloud Rou Honeybadger 000 Amazon OpsWorks Couchbase RED HAT OPENSHIFT DATA FLOWS DATABASES Microsoft Azure рп uty Amazon Workspaces NOTIFICATIONS SCHIVE IOT क Amazon Google Cloud Platform ECS Amazon rld CLOUDFOUNDRY AD IBM DB2 logz.io Microsoft Azure Service Bus £ Microsoft Azure Blob Storage TLS zendesk Launch Darkly NETWORKS Google Cloud Bigtable Direct Connect Microsoft Azure Mobile AppMicrosoft Azure Amazon Microsoft Azure Container Instan Event Hub Amazon Google Key Management Servi AmazonCloud Composer Storage Gateway Azure Data Lake Store Amazon SWF redis Amazon Buddy Elastic Beanstalk Redshift Amazon Cloud Trail Microsoft Azure *Sidekiq Flowdock REDMINE STORM Cap Twistlock SERVERLESS Azure Google MySQL M Notification Hubs MIVERED Ego Microsoft Azure IOT Hub Go SECURITY ROOKOUT Microsoft Event Viewer Microsoft Container Engine IMMUNIO Jenkins elasticsearch mongoDB. SQL Server Ganglia HTTP CHECK Atlas ANSIBLE Azure Load Balancer fluentd Bet bonsai Up Google aqua Cloud SQL ActiveMQ Microsoft .NET Azure portworx hadoop HOFF Automatio LOUDFLARE Hyper-V *Gearman Cloud loT Core VULNERABILITIES LIGHTTPD fly Ight. catchpoint™ git Java debian split bugsnag ORACLE =GO >ssh New Relic chatwork docker Neutrona Neutral On Ner Any stere Cloud Health Google TECHNOLOGIES Mac OS compute Engine Gupstart ■'MarkLogic php fpm Adobe Experience Manager Cloud Checkr PUSHER >mparticle CRI G Microso Batch SAAS amazon web services Billing HARDWARE Ruby riak 111 CISCO APPLICATION CENTRIC INFRASTRUCTURE JACO ML MODELS Google Cloud Interco PIVOTAL TRACKER pingdom OpsGenie AEROSPIKE A Amazon php pagerdutyLambda Segment ne CONTAINERS fedora fastly 00 PGBouncer DEPLOYMENT STATSU StatusPage.io MARATHON 7711 Cassandra NGUY Nagios WildFly Apache Zookeeper DNS Azure Data Factory Amazon VPC H Google Cloud Virtual Network Amazon EC2 Microsoft Azur Document D 00 OO USER ACTIVITY tHub Pivotal Container Service Amazon AWS Farcate SQL Cockroach DB Amazon CloudSearch DEV TOOLS Azure Service Bus Relay Google pache Kafka Azure HDInsight CONFIGURATION CHE Google Amazonloud Machine Learning Azure Amazon. nitive Services Auto Scaling container d SQS Azure presto Cloud Tasks Amazon мQ Aurora Microsoft Azure SQL DB SUPERVISORD Amazon CODE Elastic Load Balancing ELB Apache Zookeeper TCP RTT CHECK Google Cloud Run KONG Amazon X Ray Amazon Kinesis Data Firehose KAmazon EKS Amazon Apac WAF Alibaba Cloud Google App Engine E Exc ADENM PLATFORMS kubernetes M MQ Vault NFSSTAT puppet Amazon Linux PDH CHECK sumol moxtra Azure ERLANG Data Lake Analytics SUSE IN PostgreSQL CoreDNS Azure HAPR Microsoft Azure App Services tranfil Microsoll Event Viewer hadoop Management ATTACKERS where WORKFLOW APPS on relax Bitbucket CLOUDS cri-o CouchDB nk> DIRECTORY Signal Sciences Apache Ambari JBoss hadoop MapReduce Nextcloud hadoop BARN Akamai Rollbar TokuMX OpenLDAP syslog-ng servicenowcontainer Service APOLLO POWERDNS::: gunicorn Sentry ENGINE ceph (c) matters Windows SNMP btrfs Centos Windows Services Windows Management VERISIGN Instrumentatio VARNISH CACHE PROCES Linux Virtual Kubelet twemproxy RabbitMQ Prometheus logstash ubuntu circleci POSTFIX DISK Ding To webhooks HE building amo programy cohesive vn#6Datadog breaks down silos 媚 Unified platform Simple but not simplistic Deployed everywhere, used by everyone Breaking down silos DATADOG 6#7As we've expanded, we've solved more problems One product One platform Used by everyone Deployed everywhere Founded Datadog to break down silos Product Analytics Cloud Service Management Software Delivery Cloud Security Platform Digital Experience Monitoring Log Management Application Performance Monitoring Infrastructure Monitoring Real-time Unified Data Platform 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 DATADOG 7#8Enabling rapid innovation Real-Time Unified Data Platform 2010 Infrastructure Monitoring Hosts / Clouds / VMs / Containers/Processes/lOT 2012 FOUNDED DATADOG TO BREAK DOWN SILOS Serverless Monitoring Continuous Profiler Deployment Tracking Error Tracking Incident Management Log Management Logging without Tracing without Limits™ Synthetic Monitoring Real User Monitoring APM Limits™ Distributed Tracing Watchdog Alerts Network Performance Monitoring Mobile RUM 2017 2018 2019 2020 Cloud SIEM Application Security Management Watchdog Log Anomaly Detection Sensitive Watchdog Root Cause Analysis Data Scanner Datadog Audit Trail Session Replay Network Device Monitoring Observability Pipelines Service Cloud Security Posture Management Cloud Workload Security Database Monitoring CI Visibility Watchdog Insights Catalog Continuous Testing Cloud Cost Management Cloud Security Management SNMP Traps Universal Service Monitoring 2021 2022 Streamlined APM Onboarding RUM Heatmaps Application Vulnerability Management Data Streams Monitoring Resource Catalog Remote Configuration Datadog Teams Workflow Automation Intelligent Test Runner Netflow Monitoring Security Inbox Cloud SIEM Investigator Cloud Infrastructure Entitlement Management Mobile App Testing Cloud Vulnerability Management Dynamic Instrumentation 2023 DEPLOYED EVERYWHERE, USED BY EVERYONE DATADOG#9The Datadog platform Infrastructure Monitoring III Containers fx Serverless ** Network Performance Monitoring Network Device Monitoring Cloud Cost Management Application Performance Monitoring Digital Experience Monitoring Log Security Management Distributed Synthetics Tracing 만 Browser ☑Observability Pipelines Cloud Security Management Developer Experience SCI Visibility Service Management Incident Management Error Tracking Real User Audit Trail Application Continuous Testing Monitoring Security Workflow Automation </> Continuous EO Log Forwarding CoScreen Management Profiler Session Replay Cloudcraft Application Database ', Mobile Vulnerability Monitoring Real User Monitoring Management Universal Service ☐ Mobile App Monitoring Testing and Monitoring Cloud SIEM Sensitive Data Scanner Data Streams Monitoring Watchdog Insights Root Cause Analysis Anomaly Detection Proactive Alerts Correlation Impact Analysis Shared Platform Services Bits Al ⚫ Dashboards • Mobile • Agent ⚫ Notebook • OpenTelemetry • Service Catalog • IDE Integrations • ChatOps • SLOs • Case Management UNIFIED METRICS, LOGS, TRACES 700+ INTEGRATIONS DATADOG#10Secular tailwind of digital transformation and cloud migration Gartner Public Cloud Services Market, 2019-2027E $1,250B The Cloud market is a $560B market today, growing at a $1,000B 20% CAGR through 2027 $750B $500B $250B 20% CAGR $OB 2019 2020 2021 2022 2023 2024E 2025E 2026E 2027E Gartner Forecast: Public Cloud Services, Worldwide - 2019-2025, 4Q21 Update; 2020-2026, 4Q22 Update; 2021-2027, 4Q23 Update. DATADOG 10#11Large and growing observability TAM Gartner IT Operations Market; 2019-2027E $80B Our observability market is 11% CAGR $70B ~$51B today, growing at a $60B 11% CAGR through 2027 $50B $40B $30B $20B $10B $OB 2019 2020 2021 2022 2023 2024E 2025E 2026E 2027E Gartner Forecast: Enterprise Infrastructure Software, Worldwide - 2019-2025, 4Q21 Update; 2020-2026, 4Q22 Update; 2021-2027, 4Q23 Update. DATADOG 11#12ABILITY TO EXECUTE CHALLENGERS LEADERS Amazon Web Services Datadog New Relic Dynatrace INDUSTRY RECOGNITION We are named a Leader in the 2023 Gartner ⓇMagic Quadrant™ for Application Performance Monitoring and Observability Cisco Splunk Microsoft Honeycomb IBM Oracle Grafana Labs ServiceNow Logz.io Elastic Sumo Logic SolarWinds Broadcom Riverbed ManageEngine NICHE PLAYERS VISIONARIES COMPLETENESS OF VISION As of June 2023 © Gartner, Inc Gartner. This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Datadog. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, express or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. Gartner and Magic Quadrant are registered trademarks of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved. DATADOG#13THE FORRESTER WAVE™ Artificial Intelligence For IT Operations Q4 2022 Challengers Contenders Strong Performers Leaders Stronger current offering Weaker current offering Elastic Dynatrace Datadog ScienceLogic INDUSTRY RECOGNITION We are named a Leader in The Forrester Wave™. Artificial Intelligence for IT Operations, Q4 2022 Ranked highest for: • Product vision Market presence • Sensory/telemetry collection and retention Data insights and visualizations Splunk Micro Focus New Relic Zenoss O OpsRamp LogicMonitor O Digitate O Weaker strategy Stronger strategy Market presence OOOO The Forrester Wave™ is copyrighted by Forrester Research, Inc. Forrester and Forrester Wave are trademarks of Forrester Research, Inc. The Forrester Wave is a graphical representation of Forrester's call on a market and is plotted using a detailed spreadsheet with exposed scores, weightings, and comments. Forrester does not endorse any company, product, or service depicted in the Forrester Wave. Information is based on best available resources. Opinions reflect judgment at the time and are subject to change. DATADOG 13#14Cloud Security TAM opportunity Datadog Cloud Security market, 2019-2027E Our Cloud Security market is $40B $35B $30B $25B $20B $15B $10B $5B $OB 2019 ~$21B today, growing at a 16% CAGR through 2027 2020 2021 2022 16% CAGR 2023 2024E 2025E 2026E 2027E Gartner Forecast: Information Security and Risk Management, Worldwide - 2019-2025, 4Q21 Update; 2020-2026, 4Q22 Update; 2021-2027, 4Q23 Update. Included: Within Application Security: Application Security Testing Software; Vulnerability Assessment Software; Web Application Firewalls Software; within Cloud Security: Cloud Access Security Brokers Software; Cloud Workload Protection Platforms; within Data security: Encryption Software; Enterprise Data Loss Prevention Software, Tokenization Software; within Infrastructure Protection: Security Information and Event Management (SIEM) Software. DATADOG 14#15Why customers choose Datadog for Cloud Security Datadog enables engineering and security teams to secure their stack without sacrificing speed. $ Bring in Security with DevSecOps Empower larger set of Dev and Ops engineers to secure software they already build and observe using Datadog No performance and cost overhead; full context Unified agent, same integrations, no cost overheads, no performance overheads or coverage gaps. Customers get observability context to focus on attacks and vulnerabilities that matter. Operationalize security: Close the Loop Drive to full remediation with integrations, automation, organizational awareness and prioritization of fixes that actually matter DATADOG#16Datadog Security products Observability Infrastructure Monitoring Security Cloud Security Management Application Performance Monitoring Application Security Management Log Management Cloud SIEM DATADOG 16#17Financial overview DATADOG#18Datadog today (1) FINANCIAL $2.13B +27% FY23 revenue FY23 Y/Y growth CUSTOMERS ~27,300 Total customers 23% FY23 non-GAAP operating margin ~3,190 $100k+ ARR customers 19 PRODUCTS IN AN INTEGRATED DATA PLATFORM Infrastructure Monitoring APM Log Management Synthetic Monitoring Real User Monitoring Network Monitoring Continuous Profiler Incident Management Database Monitoring CI Visibility Observability Pipelines Workflow Automation Cloud Security Management Cloud SIEM Application Security Management Sensitive Data Scanner Universal Service Monitoring Cloud Cost Management Data Streams Monitoring 28% FY23 free cash flow margin Mid-110%s Dollar-based TTM net retention rate $2.6B Cash, cash equivalents, and marketable securities PLATFORM ADOPTION 83% Customers using 2+ products 47% Customers using 4+ products 22% Customers using 6+ products 9% Customers using 8+ products PEOPLE ~5,200 in 33 countries2 We were named a Leader in the 2023 Gartner Magic Quadrant for Application Performance Monitoring Gartner (1) All data as of Dec 31, 2023. Non-GAAP operating margin and free cash flow margin are non-GAAP measures. See Appendix for a reconciliation to financial results prepared in accordance with GAAP. (2) Employee headcount as of December 31, 2023. DATADOG 18#19Our growth drivers 1 Secular tailwind of digital transformation and cloud migration 2 Increased penetration of cloud and next-gen DevOps customers 3 Expanding products / use cases for customers 4 Adding new markets beyond observability DATADOG 19#20Rapid revenue growth Annual revenue $M's $2,500 $2,000 $1,500 $1,000 $500 198 363 603 1,029 1,675 Guided (1) 2,555-2,575 2,128 Quarterly revenue $M's Guided (1) 590 587-591 548 510 482 469 437 406 363 326 270 234 199 178 155 131 140 0 FY18 FY19 FY20 FY21 FY22 FY23 FY24 1Q20 2Q20 3Q20 4Q20 1Q21 2Q21 3Q21 4Q21 1Q22 2Q22 3Q22 4Q22 1Q23 2Q23 3Q23 4Q23 1Q24 (1) Guided revenues are forward-looking statements and speak as of February 13, 2024. See Safe Harbor for important information about these assumptions and forward-looking statements. DATADOG 20#21Strong customer growth Total customers 10,536 7,676 ~14,200 ~18,800 ~27,300 ~23,200 FY18 FY19 FY20 FY21 FY22 FY23 DATADOG 21#22Strong customer growth # of customers with ARR $1M+ 101 54 27 216 317 # of customers with ARR $100K+ % of total ARR 396 69% 76% 78% 83% 85% 86% ~3,190 ~2,780 1,228 837 438 ~2,010 FY18 FY19 FY20 FY21 FY22 FY23 FY18 FY19 FY20 FY21 FY22 FY23 DATADOG 22#234Q21 1Q22 78% 2Q22 3Q22 4Q22 1Q23 2Q23 3Q23 4Q23 81% 79% 80% 81% 81% 82% 82%83% Platform strategy is resonating with customers % of customers using 2+ products % of customers using 4+ products % of customers using 6+ products % of customers using 8+ products 40% 37% 35% 33% 42% 43% 4Q21 1Q22 2Q22 3Q22 4Q22 1Q23 2Q23 3Q23 4Q23 45% 46% 47% 10% 16% 14% 12% 18% 19% 21% 21% 22% 4Q21 1Q22 2Q22 3Q22 4Q22 1Q23 2Q23 3Q23 4Q23 4Q21 ■N 1Q22 N 2% 2% 4% 5% 6% 7% 7% 8% 9% 2Q22 3Q22 4Q22 1Q23 2Q23 3Q23 4Q23 DATADOG 23#24Strong retention and upsell Mid-high 90%s Dollar-based gross retention rate Mid- 110%s Dollar-based net retention rate DATADOG 24#25Financial summary FY18 FY19 FY20 FY21 FY22 FY23 Revenue $198M $363M $603M $1,029M $1,675M $2,128M % Y/Y growth 97% 83% 66% 70% 63% 27% Gross margin (1) 77% 76% 79% 78% 80% 82% Research & development margin(1) 27% 29% 29% 30% 30% 30% Sales & marketing margin(1) 44% 39% 31% 25% 25% 24% General & administrative margin(1) 9% 9% 8% 7% 6% 6% Operating margin (1) (3)% (1)% 11% 16% 19% 23% Free cash flow margin(¹) (3)% 0% 14% 24% 21% 28% Free cash flow(1) $(5)M $1M $83M $251M $354M $598M (1) Non-GAAP measures. See Appendix for a reconciliation of these non-GAAP measures to the most directly comparable GAAP measures. DATADOG 25#26(1) Financial outlook (as of Feb 13, 2024) Revenue 1Q24 (1) FY24 $587-591M $2,555-2,575M Non-GAAP operating income (2) $128-132M $535-555M Non-GAAP EPS (2) Weighted average diluted shares $0.33-0.35 $1.38-1.44 Approx. 357M Approx. 361M Financial outlook are forward-looking statements. See Safe Harbor for important information about these assumptions and forward-looking statements. See Appendix for information about these non-GAAP measures. DATADOG 26#27Long-term margin goal Non-GAAP % (1) 2019 2020 2021 2022 2023 Goal Operating Margin -1% 11% 16% 19% 23% 25%+ Free Cash Flow Margin 0% 14% 24% 21% 28% (1) Non-GAAP measures. See Appendix for a reconciliation of these non-GAAP measures to the most directly comparable GAAP measures. Operating Margin New Goal is a forward-looking statement and speaks as of February 15, 2024. See Safe Harbor for important information about these assumptions and forward-looking statements. DATADOG#28Capital allocation goals $) Generate healthy amounts of FCF Ensure our leadership has flexibility and capacity to invest Maintain our thoughtful and disciplined ♫ acquisition strategy DATADOG#29TAX CONSIDERATIONS Non-GAAP tax rate in 2024 and going forward 21% 2024 cash tax guided $20-25M Represents an estimated long-term projected tax rate, which is subject to change. DATADOG#30Stock-based compensation Target annual dilution related to RSUS/PSUs awarded 2.5-3.5% 2019 2020 2021 2022 2023 RSU/PSU shares awarded (M's) 4.8 4.9 5.2 7.6 7.4 % dilution on BoP 1.7% 1.7% 2.4% 2.3% basic shares Target annual dilution is a forward-looking statement and speaks as of February 15, 2024. See Safe Harbor for important information about these assumptions and forward-looking statements. DATADOG#31Appendix DATADOG#32Non-GAAP financial measures and other information The statistical data, estimates and forecasts referenced in this presentation and the accompanying oral presentation are based on independent industry publications or other publicly available information, as well as information based on our internal sources. While we believe the industry and market data included in this this presentation and the accompanying oral presentation are reliable and are based on reasonable assumptions, these data involve many assumptions and limitations, and you are cautioned not to give undue weight to these estimates. We have not independently verified the accuracy or completeness of the data contained in these industry publications and other publicly available information. We define the number of customers as the number of accounts with a unique account identifier for which we have an active subscription in the period indicated. Our ability to attract new customers will depend on a number of factors, including the effectiveness and pricing of our products, offerings of our competitors and the effectiveness of our marketing efforts. Users of our free trials or tier are not included in our customer count. A single organization with multiple divisions, segments or subsidiaries is generally counted as a single customer. However, in some cases where they have separate billing terms, we may count separate divisions, segments or subsidiaries as multiple customers. Customers as of December 31, 2022 exclude customers from a then-recent acquisition, which did not contribute meaningful revenue during the fiscal year. Other terms such as annual recurring revenue or ARR and dollar-based net revenue retention rate shall have the meanings set forth in our Annual Report. Dollar-based gross retention rate is calculated by first calculating the point-in-time gross retention as the previous year ARR minus ARR attrition over the last 12 months, divided by the previous year ARR. The ARR attrition for each month is calculated by identifying any customer that has changed their account type to a "free tier," requested a downgrade through customer support or sent a formal termination notice to us during that month, and aggregating the dollars of ARR generated by each such customer in the prior month. We then calculate the dollar-based gross retention rate as the weighted average of the trailing 12-month point-in-time gross retention rates. We believe dollar-based gross retention rate demonstrates the stickiness of the product category we operate in, and of our platform in particular. Non-GAAP Financial Measures Datadog discloses the following non-GAAP financial measures in this presentation and the accompanying oral presentation: non-GAAP gross profit, non-GAAP gross margin, non-GAAP operating expenses (sales and marketing, research and development, general and administrative), non-GAAP operating income (loss), non-GAAP operating margin, non-GAAP net income (loss), non-GAAP net income (loss) per diluted share, non-GAAP net income (loss) per basic share, free cash flow and free cash flow margin. Datadog uses each of these non-GAAP financial measures internally to understand and compare operating results across accounting periods, for internal budgeting and forecasting purposes, for short- and long-term operating plans, and to evaluate Datadog's financial performance. Datadog believes they are useful to investors, as a supplement to GAAP measures, in evaluating its operational performance, as further discussed below. Datadog's non-GAAP financial measures may not provide information that is directly comparable to that provided by other companies in its industry, as other companies in its industry may calculate non-GAAP financial results differently, particularly related to non-recurring and unusual items. In addition, there are limitations in using non-GAAP financial measures because the non-GAAP financial measures are not prepared in accordance with GAAP and may be different from non-GAAP financial measures used by other companies and exclude expenses that may have a material impact on Datadog's reported financial results. Non-GAAP financial measures should not be considered in isolation from, or as a substitute for, financial information prepared in accordance with GAAP. A reconciliation of the historical non-GAAP financial measures to their most directly comparable GAAP measures has been provided in this Appendix. Datadog defines non-GAAP gross profit, non-GAAP gross margin, non-GAAP operating expenses (sales and marketing, research and development, general and administrative), non-GAAP operating income (loss), non-GAAP operating margin and non-GAAP net income (loss) as the respective GAAP balances, adjusted for, as applicable: (1) stock-based compensation expense; (2) the amortization of acquired intangibles; (3) employer payroll taxes on employee stock transactions; (4) amortization of issuance costs; and (5) an assumed provision for income taxes based on our long-term projected tax rate. Our estimated long-term projected tax rate is subject to change for a variety of reasons, including the rapidly evolving global tax environment, significant changes in Datadog's geographic earnings mix, or other changes to our strategy or business operations. We will re-evaluate our long-term projected tax rate as appropriate. Datadog defines free cash flow as net cash provided by operating activities, minus capital expenditures and minus capitalized software development costs. Investors are encouraged to review the reconciliation of these historical non-GAAP financial measures to their most directly comparable GAAP financial measures. Datadog has not reconciled its expectations as to non-GAAP operating income, or as to non-GAAP net income per share, to their most directly comparable GAAP measure as a result of uncertainty regarding, and the potential variability of, reconciling items such as stock-based compensation and employer payroll taxes on equity incentive plans. Accordingly, reconciliation is not available without unreasonable effort, although it is important to note that these factors could be material to Datadog's results computed in accordance with GAAP. DATADOG 32#33GAAP to Non-GAAP reconciliation Gross profit margin ($000's) Revenue GAAP gross profit GAAP gross margin FY18 FY19 FY20 FY21 $198,077 $362,780 $603,466 $1,028,784 $151,548 $273,831 $473,269 77 % 75% 78% $794,539 77% FY22 $1,675,100 $1,328,357 FY23 $2,128,359 $1,718,451 79% 81% Add: Share-based compensation expense included in cost of revenue 287 582 1,794 4,565 10,827 17,578 Amortization of acquired intangibles 511 752 943 3,792 6,750 8,041 Employer payroll taxes on employee stock transactions 187 345 266 364 Non-GAAP gross profit $152,346 Non-GAAP gross margin 77 % $275,165 76% $476,193 $803,241 $1,346,200 79 % 78 % 80% $1,744,434 82% DATADOG 33#34GAAP to Non-GAAP reconciliation Operating expenses and operating profit ($000's) FY18 FY19 Revenue RESEARCH & DEVELOPMENT GAAP R&D expense $198,077 $362,780 FY20 $603,466 FY21 $1,028,784 FY22 $1,675,100 $55,176 $111,425 $210,626 GAAP R&D expense as a % of revenue 28% 31% 35% $419,769 41% $752,351 45% FY23 $2,128,359 $962,447 45% Less: Share-based compensation expense 1,641 7,972 38,008 101,942 Less: Employer payroll taxes on employee stock transactions 1,157 2,836 8,143 237,120 10,384 313,096 21,449 Add: Other Non-GAAP adj. (1) (2,344) (2,729) Non-GAAP R&D expense $53,535 $104,640 Non-GAAP R&D expense as a % of revenue 27% 29% $172,511 29% $309,684 30% $504,847 30% $627,902 30% SALES & MARKETING GAAP S&M expense $88,849 $146,657 $213,660 $299,497 $495,288 GAAP S&M expense as a % of revenue 45% 40% 35% 29% 30% $609,276 29% Less: Share-based compensation expense 1,910 5,538 20,467 35,035 76,735 101,937 Less: Amortization of acquired intangibles Less: Employer payroll taxes on employee stock transactions 284 3,756 600 6,349 825 2,766 825 5,917 Add: Other Non-GAAP adj.(1) (397) (449) Non-GAAP S&M expense $86,939 Non-GAAP S&M expense as a % of revenue 44% $141,232 39% $189,886 31% $257,513 25% $414,962 25% $500,597 24% GENERAL & ADMINISTRATIVE GAAP G&A expense $18,556 $35,889 $62,756 $94,429 GAAP G&A expense as a % of revenue 9% 10% 10% 9% $139,413 8% $180,192 8% Less: Share-based compensation expense 1,406 4,942 14,105 Less: Employer payroll taxes on employee stock transactions 19 839 22,195 1,248 38,472 49,689 830 4,811 Add: Other Non-GAAP adj. (1) Non-GAAP G&A expense $17,150 (2,266) $33,194 (2,383) Non-GAAP G&A expense as a % of revenue 9% 9% $50,195 8% $70,986 7% $100,111 6% $125,692 6% Reconciliation of operating loss and operating margin GAAP operating loss $(11,033) Add: Stock-based compensation expense 5,244 $(20,140) 19,034 Add: Amortization of acquired intangibles 511 752 $(13,773) 74,374 943 $(19,156) 163,737 Add: Employer payroll taxes on employee stock transactions 1,460 7,618 4,392 16,085 14,246 $(58,695) 363,154 7,575 $(33,464) 482,300 8,866 32,541 Less: Other Non-GAAP adj. (1) (5,007) (5,561) Non-GAAP operating (loss) income $(5,278) $(3,901) $63,601 $165,058 $326.280 $490,243 GAAP operating margin (6)% (6)% (2)% (2)% (4)% Non-GAAP operating margin (3)% (1)% 11% 16% 19% (2)% 23% (1) Non-cash benefit related to the release of a non-income tax liability DATADOG 34#35Free cash flow bridge Free cash flow ($000's) FY18 FY19 FY20 FY21 FY22 FY23 Revenue $198,077 $362,780 $603,466 $1,028,784 $1,675,100 $2,128,359 Cash flow from operations $10,829 $24,234 $109,091 $286,545 $418,407 $659,954 Capex (9,662) (13,315) (5,415) (9,956) (35,261) (27,586) Capitalized software developmental (6,176) (10,128) (20,468) (26,069) (29,628) (34,820) costs Free cash flow $(5,009) $791 $83,208 $250,520 $353,518 $597,548 Free cash flow margin (3)% 0 % 14 % 24 % 21 % 28 % DATADOG 35