Tinybird × FanDuel
Tinybird x FanDuel, real-time analytics from impossible to self-serve
Over 90% of FanDuel data engineers use Tinybird daily
Missing piece to self-serve real-time analytics platform
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Why it works
The case study earns its New Capability tag because FanDuel genuinely could not offer self-serve real-time analytics before Tinybird: their batch and streaming infrastructure existed but left a concrete gap. The story then grounds the capability in specific production deployments across multiple months, which is more convincing than a single launch claim. There is a mild coin-flip with Efficiency because the developer-experience framing also emphasizes speed of building, but the lead is firmly about standing up a net-new function.
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The month-by-month production deployment timeline (first POC in January, first production use case in April, then May, July, August) turns an abstract 'fast time-to-market' claim into a concrete, verifiable rollout cadence that readers can benchmark against their own situations.
Click to enlarge ↗ This is editorial commentary and curation. The case study, screenshot, and all metrics are Tinybird's published work; we link to the source and lead with our analysis.