Datadog, Inc. vs Elastic: Strategic Comparison

This in-depth comparison examines Datadog, Inc. and Elastic across revenue, market value, business model, competitive positioning, and long-term growth strategy. Whether you are researching Datadog, Inc. on its own, evaluating Elastic, or weighing the two companies side by side, the breakdown below highlights where each company leads and where the gap between Datadog, Inc. and Elastic is widest.

On the headline numbers, annual revenue is $3.4B (FY2025) for Datadog, Inc. and $1.7B (FY2026) for Elastic, while their respective market capitalizations stand at $96.3B and $9.3B. Both Datadog, Inc. and Elastic are headquartered in United States. Their local markets and applicable rules may still differ.

Datadog, Inc.: Datadog is the monitoring and security platform many software teams open first when something breaks. Based in New York City and founded in 2010, it collects telemetry from servers, containers, cloud services, applications and user devices, then turns it into dashboards, alerts and investigations. By mid-2026 it served roughly 33,000 customers, including about 4,720 paying $100,000 or more a year, and its annual revenue run-rate had passed $4 billion. The company is headquartered in New York City, New York.

Elastic: Elastic is the commercial company behind Elasticsearch. Retailers use it for product search, banks and governments use it to store and search security logs, and engineering teams use it to troubleshoot outages from logs, metrics and traces. Since 2023 the company has repositioned around "Search AI," selling Elasticsearch as a vector database and retrieval engine for retrieval-augmented generation (RAG) and AI agents. The parent, Elastic N.V., is incorporated in the Netherlands, but its executive office and largest operations are in the United States. The company is headquartered in Mountain View, California.

Datadog, Inc. and Elastic pursue distinct approaches to generating revenue, and understanding how each company operates is the foundation of any fair comparison between Datadog, Inc. and Elastic.

Datadog, Inc. business model: Datadog runs a B2B subscription model. Customers pay based on usage and the products they turn on: monitored hosts and containers, ingested and indexed log volume, traced requests, user sessions, security workloads, and similar units. Contracts are sold self-serve, through a direct sales team, and through cloud marketplaces such as AWS Marketplace. Revenue grows in two ways. Customers send more telemetry as their cloud footprint grows, and they add more of Datadog's products over time (the "land and expand" motion). Because spending tracks customer usage, revenue can slow when customers optimize cloud and logging costs, as happened in 2022-2023, and can accelerate when workloads such as AI applications scale up, as seen in 2026.

Elastic business model: Elastic is a B2B software company with an open-core model. Its core Elasticsearch and Kibana code is free to download, and the company makes money by selling paid subscriptions that add advanced features (machine learning, security analytics, AI assistants, enterprise support) and by running the software for customers as Elastic Cloud on AWS, Microsoft Azure and Google Cloud. Cloud customers pay largely based on consumption of compute and storage, so revenue grows as customers index and search more data. Subscriptions accounted for $1.634 billion of Elastic's $1.739 billion fiscal 2026 revenue; the rest came from professional services and training. Elastic packages the platform into three solutions: Search & AI (application search, RAG and vector search), Observability (logs, metrics, traces, APM) and Security (SIEM, XDR, endpoint protection).

The durability of a company's moat often decides long-term winners. Here is how the competitive advantages of Datadog, Inc. stack up against those of Elastic.

Datadog, Inc. competitive advantage: Datadog's main edge is breadth on one shared data platform. Metrics, traces, logs, user sessions, security signals and cost data are stored and correlated together, so a slow page can be traced from the browser session to the service, the host and the log line without switching tools. Setup is fast thanks to more than 1,000 built-in integrations and a single agent, which lets engineers adopt Datadog bottom-up before a formal enterprise purchase. Once several teams and products are in use, replacing the platform means retraining people and rebuilding dashboards, alerts and history, which creates real switching costs.

Elastic competitive advantage: Elastic's main edge is that one data store handles text search, vector search, analytics, logs and security events. Elasticsearch is built on Apache Lucene's inverted index, which makes full-text search across very large unstructured datasets fast, and the company has added dense vector search, hybrid ranking (BM25 plus vectors with reciprocal rank fusion), the ES|QL query language and Jina AI embedding and reranker models. More than a decade of open-source distribution means many engineers already know the stack, which lowers adoption friction inside large enterprises.

Future prospects matter as much as current results. The growth strategies below explain how Datadog, Inc. and Elastic each plan to expand from here.

Datadog, Inc. growth strategy: Datadog's growth plan has three parts. First, sell more products to existing customers across observability, security, and developer workflows. Second, win larger enterprise and AI-native customers that run very large workloads. Third, build AI into the platform: Bits AI agents for SRE, coding and security work, LLM Observability for teams running AI applications, and an in-house AI research group that added Adaptive ML in June 2026. Tuck-in acquisitions such as Metaplane (data observability), Eppo (experimentation) and Propolis (AI testing) extend the platform into adjacent budgets.

Elastic growth strategy: Elastic's strategy is to make Elasticsearch the retrieval layer for enterprise AI while consolidating observability and security tools onto the same platform. Recent moves include buying Jina AI (embeddings and rerankers) and Keep (AIOps alert management) in 2025, launching Elastic Workflows and Agent Builder for agentic automation, and releasing a serverless vector database in September 2026. The sales focus is on large customers: the >$100K ACV cohort grew by its largest-ever quarterly net addition in Q1 FY2027.

A closer look at the financial trajectory of Datadog, Inc. and Elastic rounds out the comparison.

Datadog, Inc.: Datadog grew revenue from $1.03 billion in 2021 to $3.43 billion in 2025. In 2025 it generated $1.05 billion of operating cash flow and $915 million of free cash flow, while GAAP net income was a much smaller $107.7 million because of heavy stock-based compensation and R&D spending. Growth accelerated in 2026: Q1 revenue was $1.006 billion (+32%) with $52.6 million of GAAP net income, and Q2 revenue was $1.12 billion (+36%) with $279 million of free cash flow. After Q2, management guided to full-year 2026 revenue of about $4.45-4.47 billion, roughly 30% growth. GAAP operating income stays near break-even, while non-GAAP operating margin runs in the low 20s. Datadog, Inc. is a dominant player in cloud monitoring and security, sustaining a market valuation generally exceeding $35 billion.

Elastic: Elastic's revenue grew from $862 million in fiscal 2022 to $1.739 billion in fiscal 2026. FY2026 subscription revenue was $1.634 billion (+18%), and sales-led subscription revenue, which excludes monthly self-serve cloud, was $1.438 billion (+20%). Non-GAAP operating income reached $285 million (16.4% margin) and adjusted free cash flow $346 million (20% margin), though GAAP operating loss was $33 million. GAAP net income of $367.8 million was lifted by a fourth-quarter income tax benefit, since the company's operations were not profitable on a GAAP basis. In Q1 FY2027 (ended July 31, 2026) revenue rose 15% to $478 million, cRPO grew 21% to $1.153 billion, and Elastic raised FY2027 revenue guidance to $1.998-$2.010 billion. Elastic N.V. is a major search and observability enterprise software company, sustaining a market valuation typically over $7 billion.