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Alluxio Raises $50M in Financing for Data Orchestration

November 22, 2021
Alluxio Raises $50M in Financing for Data Orchestration
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SAN MATEO, Calif. — Alluxio raised $50 million in Series C financing to help fund its open source data orchestration software for large-scale analytics and artificial intelligence (AI)/machine learning (ML) workloads.

The over-subscribed funding round was led by an unnamed global investment firm, along with participation from existing investors, including a16z, Seven Seas Partners, and Volcanics Ventures, according to Alluxio this month.

To date, Alluxio has raised over $70 million.

Alluxio will use the funds to continue “fueling its rapid growth” by investing in expanded product capabilities as well as scaling go-to-market and engineering operations across the globe.

The company is also expanding its Asia-Pacific presence with the opening of an office in Beijing, China.

Alluxio’s software is designed to enable data teams to separate compute from storage, while bringing data closer to compute for analytics and AI/ML workloads — spanning clouds, clusters, and regions. Intelligent data tiering and caching are two of the platform’s features to improve performance and reliability.

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Eight of the 10 largest internet companies use Alluxio, including Facebook, Uber, and Alibaba, with “many more of the largest enterprises” running its software in production, according to the company.

“To stay competitive, leading companies in all sectors are in their digitalization journey,” said Haoyuan Li, founder and CEO, Alluxio. “In this, more and more enterprise architectures have shifted to hybrid and multicloud environments for data-driven applications.

“While this shift allows for more flexibility and agility, it also means having to separate compute from storage, creating new challenges in how data needs to be managed and orchestrated across frameworks, clouds, and storage systems.

“The funding will help us further catalyze our growth and global expansion plan, as we help more businesses solve the most complex data challenges in today’s world.”

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