Datadog today introduced its Storage Management product, a tool that gives teams granular visibility into Amazon S3 usage and, in preview, Google Cloud Storage and Azure Blob. The solution automatically surfaces waste, flags anomalous patterns, and recommends actions that can reduce spend at the bucket and prefix level across billions of objects.
The new feature is designed to tackle the steep rise in cloud object storage costs that accompanies data‑intensive and AI workloads. By providing real‑time insights and automated remediation, the tool helps companies keep storage budgets in check while still supporting the large training datasets, model artifacts, and inference logs that drive AI innovation.
Datadog’s Q3 2025 financials underscore the strategic importance of this launch. Revenue climbed 28.4% year‑over‑year to $885.7 million, and non‑GAAP EPS rose to $0.55, beating analyst expectations by $0.10. The company raised its full‑year guidance for revenue and operating income, reflecting confidence in continued demand for its observability and cost‑optimization platforms. The strong results were driven by a 30% increase in customers with annual recurring revenue above $100,000 and a 4% rise in overall ARR, indicating robust adoption of its core services.
The cloud object storage market is projected to grow from $9.44 billion in 2025 to $16.69 billion by 2034, a 15.3% CAGR. AI workloads are a key driver, with 62% of organizations reporting budget overruns in the past year. Datadog’s new tool positions it against competitors such as CloudHealth, Cloudability, and native cloud provider cost‑management services, offering deeper integration with observability data and a broader platform ecosystem. Early adopters report that the tool has already identified $2 million in potential savings in a single month of use.
By expanding its Cloud Cost Management suite, Datadog is reinforcing its strategy to become the go‑to platform for end‑to‑end cloud efficiency. The Storage Management product not only opens a new revenue stream but also strengthens customer stickiness, as teams that rely on Datadog for monitoring and security are now able to manage storage costs within the same interface. The company’s leadership views the launch as a critical step toward capturing a larger share of the growing cloud‑efficiency market.
VP of Product Yrieix Garnier said the tool “empowers companies building AI products to optimize cloud storage costs and prevent unexpected spend.” He added that data storage and processing often exceed the cost of model training and inference, underscoring the product’s relevance to the AI‑heavy customer base.
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