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Now Available: GPU Droplets

Access greater computing power with DigitalOcean's GPU Droplets, now available on-demand starting at $2.99/GPU/hour. Experience affordable, high-performance AI infrastructure designed for developers and startups.

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From simple tools and predictable pricing to support designed for growing businesses, DigitalOcean's cloud is built to serve the unique needs of startups and SMBs.

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DigitalOcean's blend of intentional simplicity, affordability and flexibility in its cloud services makes it an appealing option for individual developers, high growth startups, and more generally ISVs and SMEs (small and medium enterprises) seeking a robust platform alternative from the hyperscalers. It's a business ready cloud - making it easy for growing companies to attain momentum and scale sustainably.
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Research Vice President, IDC

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Creating a first-of-its-kind video platform as a startup is a near impossible task without partners that are not only tremendously talented, but have the same forward thinking as you do. DigitalOcean has helped us go from architecture to launch by pairing us with strategic partners who are like-minded and innovative.
Denny Darmo

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Founder and CEO, Snipitz

The cost of running ScraperAPI would be 250% more on AWS, as compared to DigitalOcean.
Zoltan Bettenbuk

Zoltan Bettenbuk,

CTO, ScraperAPI

The high availability control plane is a great addition, as it means we can be even more confident in the availability of hardware provided by you. We've never had an availability issue from DigitalOcean.
Stephen Lazarionok

Stephen Lazarionok,

Co-Founder, CTO, Zingbrain AI

We soon found out that the service we received from DigitalOcean was the best in terms of stability of the Droplets and the bandwidth, and all of the network that comes out of the data centers. It's very stable. This is the key point, and that stability has helped us to increase our volume as well.
We chose DigitalOcean Kubernetes because we like simplicity. In the beginning, we had a small team and didn't have the resources to manage a Kubernetes cluster. We wanted to spend time developing the product instead of managing infrastructure.

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