Rowy vs Datadog
Side-by-side comparison of AI visibility scores, market position, and capabilities
Rowy is an open-source low-code platform for building backend automations and internal tools on top of Firestore and Google Cloud with a spreadsheet-like UI.
About
Rowy is an open-source low-code backend platform that brings a spreadsheet-like table interface to Firestore databases, allowing developers and technical team members to build backend automations, internal tools, and data management workflows directly on top of their Firebase and Google Cloud infrastructure. The platform renders Firestore collections as interactive tables with typed columns, inline editing, filtering, and sorting, transforming a schema-less database into a structured data management interface that non-developers can use without direct Firestore access or custom admin tooling. Each column in a Rowy table can be backed by a cloud function that executes custom logic when data changes — image processing, API enrichment, notification dispatch, or record validation — turning the spreadsheet interface into a visual programming environment for data-driven automation.
Cloud observability leader with $2.68B ARR; 750+ integrations; expanding into AI/LLM monitoring as enterprises instrument generative AI workloads at scale in 2025.
About
Datadog is a cloud-native monitoring and security platform founded in 2010 by Olivier Pomel and Alexis Lê-Quôc, headquartered in New York City. The company went public on Nasdaq (DDOG) in September 2019 and has grown to serve over 29,000 customers as of FY2024, generating $2.68 billion in annual recurring revenue, representing approximately 26% year-over-year growth. Datadog's platform spans infrastructure monitoring, application performance management (APM), log management, security monitoring, and AI observability, positioning it as the unified observability stack for cloud-scale engineering teams.
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