Jellyfish vs Datadog
Side-by-side comparison of AI visibility scores, market position, and capabilities
Raised $71M total including Series B led by Accel. Active 2026 growth as CFOs demand engineering efficiency metrics. Connects Jira, GitHub, and financials to show ROI of engineering investment. 1M+ engineers tracked.
About
Jellyfish is an engineering intelligence platform that maps engineering work to business outcomes — connecting Jira tickets, GitHub commits, deployment data, and financial investment to show executive leadership the return on engineering spending. The company has raised $71 million in total including a Series B led by Accel, serving enterprises who need to demonstrate that software engineering investment is generating measurable business value.
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.
AI Visibility Head-to-Head
Capabilities & Ecosystem
Capabilities
Integrations
Also Compare
Track AI Visibility in Real Time
Monitor how your brand performs across ChatGPT, Gemini, Perplexity, Claude, and Grok daily.