Backblaze, Inc., the cloud storage innovator providing a modern alternative to traditional cloud providers, announced Backblaze B2 Overdrive, a high-performance cloud storage solution delivering terabit-speed throughput starting at $15 per terabyte—a fraction of competitors’ costs.
Built for organizations pushing the limits of data throughput performance, B2 Overdrive eliminates the all-too-common compromise between performance and economics that has constrained data-intensive workloads.
“Today’s AI, machine learning, and high-performance compute workloads demand both lightning-fast access to massive datasets and predictable economics that don’t penalize success,” said Gleb Budman, CEO at Backblaze. “With B2 Overdrive, we’re challenging the industry’s assumption that organizations must pay colossal prices for colossal performance. We’ve engineered a solution that delivers the sustained high-throughput organizations need, without the egress fees and complex pricing tiers that are pervasive of legacy providers.”
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B2 Overdrive builds on Backblaze’s always-hot cloud storage infrastructure with expanded networking and storage capabilities that enable sustained throughput up to a terabit per second. It transforms high-performance cloud storage from a cost center into a strategic advantage, by delivering:
- Terabit speed at exabyte scale: Up to a terabit per second throughput enabling rapid processing of exabyte-scale datasets without complex architectures.
- Free egress: Move data freely to any GPU cloud or high performance compute cluster with unlimited free egress.
- Private networking support: Transfer data at maximum speed through secure private networking connections to your infrastructure.
“We need to store an insane amount of data and, at the same time, download it to different GPU clusters around the world, and for all that to not cost an insane amount of money. That’s why we chose Backblaze,” said Dean Leitersdorf, CEO and co-founder of generative AI platform Decart. B2 Overdrive is designed for a wide range of throughput-intensive use cases, including AI/ML training and inference, high-performance compute, large-scale data analytics, media processing pipelines, research compute, and content delivery.
Source: BusinessWire