#1DATADOG May 2022#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 and the accompanying oral presentation speak 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, growth in and ability to capitalize on long-term market opportunities, gross margins and operating margins including with respect to sales and marketing, research and development expenses, investments and capital expenditures, and Datadog's future financial performance, including its guided revenue on the slide "Rapid Revenue Growth" and the information on the slide entitled "Financial Outlook". 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 business depends on our 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; (12) general market, political, economic, and business conditions; and (13) the impact that the ongoing COVID-19 pandemic and any related economic downturn could have on our or our customers' businesses, financial condition and results of operations. 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 Annual Report on Form 10-K for the year ended December 31, 2021, filed with the SEC on February 25, 2022. Additional information will be made available in our Quarterly Report on Form 10-Q for the quarter ended March 31, 2022 and in 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 of this press release. We disclaim any obligation to update forward-looking statements. DATADOG 2#3Datadog is the monitoring and security platform for cloud applications 3#4Evolving technology paradigms create rising complexity Diversity of technologies in use Number of technologies and tools Frequency Standardized/On-prem Frequency of releases Few vendor suites Waterfall DATADOG Once a year X Once a day Lots of open source and SaaS Time Diverse/Cloud On-demand Time Agile X X Scale in number of computing units Number of nodes Static People Number of people involved Physical hardware Siloed Ops Cloud instances X Dev + Ops Serverless & microservices Containers Business + Dev + Ops Time Dynamic Security + Dev + Ops + Business Time Integrated 4#5Datadog solves complexity redisyon s ROOKOUT Event Viewer Container Engine IMMUNIO HTTP CHECK Google MySQL Mierande SQL Server Active MO Microsoft M.NET Google Cloud SQL Gangila ANSIBLE Azure REDMINE Sidekiq Flowdock Mac OS X Google mongoDB. At as compute Engine upstart Jenkins elasticsearch portworx AutomationLOUDFLARE aqua hadoop ORACLE -GO >ssh CloudHealth Amazon Kinesis Amazon Buddy Elastic Beanstalk git Odebian split bugsnag Twistlock ( PUSHER Azure Load Balancer Hyper-V #Gearman php fpm PostgreSQL CRI Cloud Checkr C php fluentd bonsai UP LIGHTIPD catchpoint Amazon S3 etcd > Java N Amazon Redshift Amazon ALB Couchbase pagerdutya STORM CCapistrano Azure M Notification Hubs a Microsoft Azure TOT Hub Cloud lo Amazon OpsWorks New Relic chatwork dockerriak Neutrona Mark Logic Microsoft Azure Microsoft Azure Container Instance Google Event Hub Cloud APIs 3 Amaz EMR mongoDB Adobe Experience >mparticle pingdom Manager Microsoft Azure Table Storage www journald OpsGenie A Amazon Lambda Segment RED HAT OPENSHIFT PIVOTAL TRACKER amazon web services SERVERLESS Villware vSphere Dy SAAS Microsoft Azure Batch Service HARDWARE Ruby CONVOX Microsoft DATABASES Queue St MESOS SECURITY amazon web services Apache Solr Biling Google 1.1. Cloud Interconnect CISCO APPETICE EVR neo4j Azure Strear ealytics fastly fedora SYSLOG Teams Apache Zookeeper Google Cloud Dataproc Amazon Nomad CONTAINERS 688 Amazon Microsoft Azure SES Google App Service Environment Cloud Memorystore for Regis CO Azure NETWORK STATSD MARATHON Groups RIGOR CA O StatusPage.io DNS NOTIFICATIONS SYSTEM DEPLOYMENT IOT Google Coud TPU APPS CONSUL Cassandra python Google Cloud Par Su Gremlin VictorOps NGINX Nagios WoFy JBoss Amazon Amazon SOS CadeDeploy slack Amazon Amazon DynamoDB DocumentDB NETWORKS Azure Event Grid Orhantonn METRONICO Launch Darkly CLOUDS Apache Ambari ECS Google Cloud Platform Amazon AD DEV TOOLS papertrail WORKFLOW RBL TRACKER CODE Microsoft Azure VM Google Cloud Bigtable rosoft Azure obile AppMicrosoft Azure Logle App OPENMETRICS PLATFORMS træfik Ho 2000 CONFIGURATION on Things Akamai Amazon Polly Elastic Load Balancing ELB websphere cure asement TLS cri-o CouchDB salesforce desk splunk> 000 nextcloud DIRECTORY Signal Sciences CLOUDFOUNDRY IBM DB2 Google hauts Chat Azure Key Vault Amazon Route 53 GitHub Cockroach DB zendesk IBM MQ INDO Micsot Event Viewer Microsoft Azure Blob Storage NTP Anache Kafka TO TeamCity Rollbar H 02 Pivotal Container Service Azure Service Bus Relay Apache Zookeeper Vault Microsoft Azure App Services TCP Azure Application Gaceway Mitmolt Ane SQL Elastic Pool logz.io Spark ERLANG Core OS Marsuit Azure Service Bus Amazen Azure Cognitive Services Auto Scaling Azure Data Factory Amazon CloudSearch Azure Honight kubernetes TCP RTT CHECK Google Cloud Run TokuMX syslog-ng Amazon Google CloudHSM Cloud Firestore SQL Azure Amar Data Lake Store AmazonCloud Composer Storage Gateway SWF Amazon VPC My Microsoft Azure Azur ustomers DB for MySQL al Servi Azure Amazon X Ray NFSSTAT puppet AWS Fargare PDH CHECK Google Cloud Tasks SUPERVISORD Amazon API Gateway PostgreSQL Google Amazon Cloud Virtual Network EC2 containerd sos Azure presto KONG SQL Microsoft Azure SQL DB Linux hepojop OpenLDAP gunicorn ceph (x) matters Windows 8 SNMP btrfs Windows Management CentOS Windows Services instrument VERISIGN RabbitMQ twemproxy logstash ubuntu > circlecl Amazon Kinesis Data Firehose Amazon EKS APOLLO POWERDNS::: Sentry ENGINE Ace CommesOR SI Amazon Google Key Management Servi VARNISH CHE Google Amazon oud Machine Learning moxtra SUSE CoreDNS servicenowfontainer Service PROCES Virtual Kubelet Google Cloud Rou Honeybadger Amazon Amazon MQ Aurora GHE R Microcaft Azum Document D Amazon Apac Alibaba Cloud WAF Azure Data Lake Analytics Linux Google App Engine Azure E Exc sumolo IX N HAPR POSTFIX DISK Ding Ta webhooks HE 5 vns#6Datadog breaks down silos Unified platform Simple but not simplistic DATADOG Deployed everywhere, used by everyone Breaking down silos#7Our history of innovation Founded Datadog to break down silos Real-Time Unified Data Platform 2010 2011 Infrastructure Monitoring (2012) DATADOG 2012 2013 2014 2015 2016 APM (2017) 2017 Logs (2018) 2018 Security Platform (2020) User Experience Monitoring (2019) 2019 2020 2021 2022 One product One platform Used by everyone Deployed everywhere 7#8Our history of innovation Real-Time Unified Data Platform 2010 2011 DATADOG Infrastructure Monitoring Hosts / Clouds / VMs / Containers / Processes / lot 2012 2013 2014 Founded Datadog to break down silos 2015 2016 APM Distributed Tracing 2017 Log Tracing without Management Limits™ Logging without Limits™ Watchdog Alerts Serverless Monitoring 2018 Network Performance Monitoring Continuous Profiler 2019 Deployment Tracking Synthetic Error Monitoring Tracking Real User Monitoring Cloud SIEM Mobile RUM Session Replay Incident Management Database Monitoring CI Visibility Watchdog Root Cause Analysis 2020 Network Device Monitoring Cloud Security Posture Management Cloud Workload Security Watchdog Insights 2021... Deployed everywhere, used by everyone 8#9At our core, Observability is a very large opportunity $53B in 2025 Gartner Forecast: Enterprise Infrastructure Software, Worldwide, 2019-2025, 3Q21 Update, published September, 2021. DATADOG $38B 2021 $42B 2022 $45B 2023 $49B 2024 $53B 2025 9#10Our security opportunity DATADOG Developers Security DevSecOps Operations 10#11Financial overview 11#12Datadog today FINANCIAL (¹) $1.19B +78% TTM revenue TTM Y/Y growth 19% TTM non-GAAP operating margin 28% TTM free cash flow margin 130%+ Dollar-based net retention rate for 19 consecutive quarters $1.7B Cash, cash equivalents, restricted cash, and marketable securities CUSTOMERS ~19,800 Total ~2,250 $100K+ ARR PLATFORM ADOPTION 81% Customers using 2+ products 35% Customers using 4+ products 12% Customers using 6+ products 14 PRODUCTS IN AN INTEGRATED DATA PLATFORM Infrastructure Continuous Profiler PEOPLE Synthetic Monitoring Database Monitoring Log Management Network Monitoring Cloud Security Posture Management ~3,200 at 31 locations Incident Management CI Visibility APM Real User Monitoring Cloud SIEM Cloud Workload Security Application Security Monitoring We were named a Leader in the 2021 Gartner Magic Quadrant for Application Performance Monitoring Gartner. (1) All data as of Mar 31, 2022. Non-GAAP operating margin and TTM 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, 2021. DATADOG 12#13Financial highlights → Large and growing TAM opportunity → Rapid growth at scale Growing multi-product customers → 130%+ dollar-based net retention rate in each of the past nineteen quarters ▸ Strong business model efficiencies DATADOG 13#14Rapid revenue growth Annual revenue $M's 101 198 74% CAGR 363 604 Guided (¹) 1,600-1,620 1,029 Quarterly revenue $M's 40 46 51 62 70 83 96 114 FY17 FY18 FY19 FY20 FY21 FY22 (1) Guided revenue are forward looking statements. See Safe Harbor for important information about these assumptions and forward looking statements. DATADOG 131 140 155 178 199 234 270 326 Guided (¹) 376-380 363 1Q18 2018 3Q18 4Q18 1Q19 2Q19 3Q19 4Q19 1Q20 2Q20 3Q20 4Q20 1Q21 2Q21 3Q21 4Q21 1Q22 2Q22 14#15Strong customer growth Total customers 5,403 FY17 DATADOG 7,676 FY18 10,536 FY19 ~14,200 FY20 ~18,800 FY21 ~15,200 1Q21 ~19,800 1Q22 15#16Strong customer growth # of customers with ARR $1M+ 11 FY17 DATADOG 27 FY18 54 FY19 101 FY20 216 FY21 # of customers with ARR $100K+ % of total ARR 78% 60% 236 FY17 69% 438 FY18 76% 837 FY19 1,228 FY20 83% ~2,010 I FY21 79% 1,406 1Q21 85% ~2,250 1Q22 16#17Platform strategy is resonating with customers % of customers using 2+ products 62% 68% 71% 72% 75% 75% DATADOG 77% 78% 81% 1020 2020 3Q20 4Q20 1Q21 2Q21 3Q21 4Q21 1Q22 % of customers using 4+ products 12% 15% 20% 22% 25% 28% 31% 33% 35% 1020 2020 3020 4Q20 1Q21 2Q21 3Q21 4Q21 1Q22 % of customers using 6+ products 3% 4% 10% 12% 1020 2020 3Q20 4Q20 1Q21 2Q21 3Q21 4Q21 1Q22 17#18Strong retention and upsell DATADOG Mid-High 90%s Dollar-based gross revenue retention rate 130%+ Dollar-based net revenue retention rate for 19 consecutive quarters 18#19Financial summary Revenue % Y/Y growth Gross margin (¹) Research & development margin (¹) Sales & marketing margin(¹) General & administrative margin(¹) Operating margin(¹) Free cash flow margin(¹) Free cash flow (¹) FY17 $101M 109% DATADOG 77% 23% 43% 10% 1% 6% $6M FY18 FY19 $198M $363M 97% 77% 27% 44% 9% (3)% (3)% $(5) M 83% 76% 29% 39% 9% (1)% 0% $1M (1) Non-GAAP measures. See Appendix for a reconciliation of these non-GAAP measures to the most directly comparable GAAP measures. FY20 $603M 66% 79% 29% 31% 8% 11% 14% $83M FY21 $1,029M 70% 78% 30% 25% 7% 16% 24% $251M TTM (Mar-22) $1,193M 78% 79% 29% 24% 6% 19% 28% $336M 19#20Financial outlook (as of May 5, 2022) (¹) Revenue Non-GAAP operating income (2) Non-GAAP EPS(2) Weighted average diluted shares 2Q22 DATADOG $376-380M $49-53M $0.13-0.15 Approx. 347M FY22 $1,600-1,620M $240-260M $0.70-0.77 Approx. 349M (1) Financial outlook are forward looking statements. See Safe Harbor for important information about these assumptions and forward looking statements. (2) Non-GAAP measures. See Appendix for a reconciliation of these non-GAAP measures to the most directly comparable GAAP measures. 20#21Appendix 21#22Non-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. Terms such as number of customers, 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) non-cash benefit related to tax adjustment; (4) employer payroll taxes on employee stock transactions; and (5) amortization of issuance costs. 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 22#23GAAP to Non-GAAP reconciliation Gross profit margin ($000s) Revenue GAAP gross profit GAAP gross margin Add: Share-based compensation expense included in cost revenue Amortization of acquired intangibles Employer payroll taxes on employee stock transactions Non-GAAP gross profit Non-GAAP gross margin DATADOG FY17 $100,761 $77,347 77% 112 484 $77,943 77% FY18 $198,077 $151,548 77% 287 511 $152,346 77% FY19 $362,780 $273,831 75 % 582 752 $275,165 76% FY20 $603,466 $473,269 78 % 1.794 943 187 $476,193 79 % FY21 $1,028,784 $794,539 77% 4,565 3,792 345 $803,241 78% TTM (Mar-22) $1,193,265 $931,224 78% 5,517 4,850 352 $941,943 79 % 23#24GAAP to Non-GAAP reconciliation Operating expenses and operating profit ($000s) FY17 $100,761 Revenue RESEARCH & DEVELOPMENT GAAP R&D expense GAAP R&D expense as a % of revenue Less: Share-based compensation expense Less: Employer payroll taxes on employee stock Insactions Add: Other Non-GAAP adj.(1¹) Non-GAAP R&D expense Non-GAAP R&D expense as a % of revenue SALES & MARKETING GAAP S&M expense GAAP S&M expense as a % of revenue Less: Share-based compensation expense Less: Amortization of acquired intangibles Less: Employer payroll taxes on employee stock transactions Add: Other Non-GAAP adj. (1) Non-GAAP S&M expense Non-GAAP S&M expense as a % of revenue GENERAL & ADMINISTRATIVE GAAP G&A expense GAAP G&A expense as a % of revenue Less: Share-based compensation expense Less: Employer payroll taxes on employee stock transactions Add: Other Non-GAAP adj. (1) Non-GAAP G&A expense Non-GAAP G&A expense as a % of revenue Reconciliation of operating income and operating margin GAAP operating (loss) income Add: Stock-based compensation expense Add: Amortization of acquired intangibles Add: Employer payroll taxes on employee stock transactions Less: Other Non-GAAP adj. (1) Non-GAAP operating income GAAP operating margin Non-GAAP operating margin (1) Non-cash benefit related to the release of a non-income tax liability DATADOG $24,734 25% 1,160 $23,574 23 % $44,213 44% 977 $43,236 43% $11,356 11% 819 $10,537 10% $(2,956) 3,068 484 $596 (3)% 1% FY18 $198,077 $55,176 28 % 1,641 $53,535 27% $88,849 45 % 1,910 $86,939 44% $18,556 9% 1,406 $17,150 9 % $(11,033) 5,244 511 $(5,278) (6)% (3)% FY19 $362,780 $111,425 31 % 7,972 1,157 (2,344) $104,640 29% $146,657 40 % 5,538 284 (397) $141,232 39 % $35,889 10% 4,942 19 (2,266) $33,194 9% $(20,140) 19,034 752 1,460 (5,007) $(3,901) (6)% (1)% FY20 $603,466 $210,626 35 % 38,008 2,836 (2,729) $172,511 29 % $213,660 35 % 20,467 3,756 (449) $189,886 31% $62,756 10 % 14,105 839 (2,383) $50,195 8% $(13,773) 74,374 943 7,618 (5,561) $63,601 (2)% 11% FY21 $1,028,784 $419,769 41 % 101,942 8,143 $309,684 30 % $299,497 29% 35,035 600 6,349 $257,513 25 % $94,429 9% 22,195 1,248 $70,986 7% $(19,156) 163,737 4,392 16,085 $165,058 (2)% 16 % TTM (Mar-22) $1,193,265 $491,111 41% 130,569 9,669 $350,873 29 % $336,310 28% 42,620 803 6,279 $286,608 24% $99,715 8% 23,054 1,381 $75,280 6% $4,088 201,760 5,653 17,681 $229,182 -% 19 % 24#25Free Cash Flow bridge Free Cash Flow ($000s) Revenue Cash flow from operations Capex Capitalized software developmental costs Free cash flow Free cash flow margin DATADOG FY17 $100,761 $13,832 (2,351) FY18 $198,077 $362,780 6% $10,829 $24,234 (9,662) FY19 (5,452) $6,029 $(5,009) (3)% (13,315) (5,415) (6,176) (10,128) (20,468) $791 FY20 0 % $603,466 $1,028,784 $109,091 $83,208 FY21 14 % $286,545 (9,956) (26,069) $250,520 24 % TTM (Mar-22) $1,193,265 $382,283 (18,472) (27,859) $335,952 28 % 25