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Glenn Kaonang · · 4 min read

Databricks’ under-the-radar Asian rival

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Hello reader,

The AI boom is creating an unexpected winner: companies that convince enterprises they can handle everything data-related on one platform.

One of them is Databricks. The company recently announced that it had surpassed a US$5.4 billion revenue run rate, fueled partly by US$1.4 billion from “AI products” that didn’t exist a few years ago.

Interestingly, there’s a little-known Singaporean startup that’s quietly trying to chip away at Databricks’ dominance and carve out its own territory in Asia. It’s called Singdata, and it was founded by industry veterans from Alibaba Cloud.

I’ll admit: I hadn’t heard of Singdata before reporting this story, and neither had the three industry analysts I asked. Yet this company has managed to raise funds from investors like Granite Asia. It also counts social media firm Xiaohongshu and logistics provider NinjaVan as clients and bills itself as the “Databricks of Asia.”

Our first top story today dives deeper into Singdata and why the company believes it has a chance at competing with Databricks. It’s worth taking a closer look at, given that Singdata is built on the foundation of something Databricks struggles with: seamlessly supporting both US and Chinese cloud providers.

Singdata’s future could signal whether Asian-built enterprise tech can compete with Silicon Valley – or if geography matters less than we think.

Glenn Kaonang, journalist


Top Stories

1️⃣ Ex-Alibaba team builds Asia’s answer to Databricks

Image credit: Arsal Ysfin

Singdata believes it can offer Asian enterprises a cheaper yet better alternative when it comes to maintaining an in-house data stack. Co-founder and CEO Ethan Yu says that since using his company’s data platform, Xiaohongshu has been able to profile its customers in near real time while slashing infrastructure costs by around a third.

But given Databricks’ increasing dominance, Singdata’s success hinges on whether more companies will adopt hybrid cloud strategies and split their workloads between US and Chinese cloud providers.


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Glenn Kaonang