Sisense vs Datadog
Side-by-side comparison of AI visibility scores, market position, and capabilities
NYC embedded analytics and BI unicorn at $184.8M 2024 revenue (+32% YoY) with 2,000+ customers (eBay/UiPath/Wix); $274M total (Series F 2020 $1B+ valuation) with Sisense Intelligence GenAI competing with Looker for embedded SaaS analytics.
About
Sisense is a New York City-based embedded analytics and business intelligence platform — backed with $274 million in total funding with unicorn status ($1 billion+ valuation) achieved in January 2020 Series F — providing approximately 2,000 enterprise customers with AI-powered analytics tools for embedded BI (the analytics SDK that SaaS companies embed in their products for customer-facing reporting) and internal business intelligence for non-technical business users. In 2024, Sisense reported $184.8 million in revenue (up from $140 million in 2023). The platform — comprising Fusion Embed (white-label embedded analytics), Compose SDK (developer API for custom analytics applications), and Sisense Cloud (hosted BI platform) — serves enterprise customers including eBay, UiPath, Wix, Tinder, Philips, and Nasdaq. In 2024, Sisense launched Sisense Intelligence (GenAI analytics suite including AI-generated explanations and forecasting features). The company experienced a significant data breach in April 2024 and implemented workforce reductions in 2022 and 2024. Founded in 2004 in Tel Aviv, Israel.
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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