Cost-effective dataset storage with the performance you need for generative AI models.

Storing and distributing large amounts of AI training data, models, and output can present storage and distribution challenges. Storj provides consistently high performance globally at a fraction of the cost of legacy, centralized cloud storage providers.

Unlimited scale within your budget.

With Storj, you can seamlessly expand your storage as models become more complex and demand grows while benefiting from predictable, low costs.

Security, privacy, and control.

Delegated credential-level authorization puts you in control of your data. And end-to-end encryption of data and metadata means the highest levels of security and privacy for your proprietary datasets.

Unparalleled data resiliency.

Automated data orchestration between satellites and thousands of globally diverse nodes means you get built-in multi-region support, 11 9’s of durability and 99.95% availability—anytime, anywhere.

Consistent global performance.

Parallelism is used to pull the fastest segments for file reconstitution. Download speeds are consistent and fast from anywhere in the world—without the need for additional multi-region storage costs.
Cost Comparison AWS to Storj
The figure above shows the one month cost to store and retrieve a data set 1x based on the standard retail price published on the providers’ publicly available pricing web page.

Storing and Distributing AI Training Data and Models

Working with some of our partners including Hugging Face and VALDI, we've analyzed different data and distribution-heavy workloads of the generative AI space to compare the performance, cost and other factors involved in the storage and distribution of the required data. The math is pretty simple. And compelling. Storj customers are often able to shave a zero off of their cloud storage bills with high performance and security.

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Store your data sustainably.

Instead of building power-hungry data centers, Storj makes use of existing, unused hard drive capacity. Data is encrypted, split and distributed across tens of thousands of endpoints in 100+ countries. With no need for data centers, manufacturing hard drives or replicating data for multi-region access and durability, Storj is dramatically cleaner than traditional cloud storage -up to 83% cleaner.

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“We were impressed with Storj’s out-of-the-box performance in moving large datasets, which we feel is a direct benefit of the way its decentralized network is structured. The excellent download speeds that we observed from locations that were far away from the upload location is extremely valuable to us.”
Antonin Portelli
Antonin Portelli
Professor at the University of Edinburgh

Learn how Storj is being used for high performance computing.

DiRAC is a multi-university research consortium working on high energy particle physics and cosmology that requires computer simulations on large scale supercomputers with a workflow that has to handle enormous datasets. The team needed to be able to store these high-value datasets on a long-term basis with high resilience. Plus, they needed to share them in a performant way with the globally disparate team. Storj fit their criteria.

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