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Store, protect, process and serve any data with one single software-defined solution


  1. Overview
    OpenIO overcomes all the limitations of traditional object stores while offering better functionalities.
  2. Store
    • Scale-out by nature. A shared nothing model aggregates capacity from independent x86 and ARM servers.
    • Limitless storage based on open source technology.
    • Store 1,000+ PBs of data and hundreds of billions of objects.
  3. Protect
    • Data Replication with multiple copies, local and/or remote.
    • Reed-Solomon Erasure Coding.
    • Various topologies from a single data center to multiple or stretched clusters across geos.
  4. Process
    • Install and run applications where data resides.
    • Better application SLAs with data locality.
    • Flexible application support with APIs, file-based access, or SDKs.
    • Unparalleled TCO reduction.
  5. Serve
    • Native Object APIs: C, Python, and Java.
    • Standard Object APIs: OpenIO REST/HTTP, Amazon S3 and OpenStack Swift.
    • Multiple file sharing and access methods: NFS, SMB, FTP and local FUSE.

Go beyond object storage

What differentiates OpenIO is that it scales quicker, more transparently and without constraints compared to other solutions we have tested.
Alan Martins, VP Infrastructure Dailymotion

Transform Your Storage Infrastructure

  • Ease of use

    Easy to test, deploy, manage, and use. New hardware is automatically discovered and can be used immediately. Data is automatically routed and load-balanced to the best available nodes.

  • Unparalleled scalability

    Start small and grow with your needs. Scalability is simple and efficient: easily add one node or hundreds. Deploy as you grow, by small or large increments: the choice is yours.

  • Total freedom

    Auto-adaptive, not just hardware agnostic. OpenIO has built-in support for heterogeneous hardware within the same cluster. Each node is used to its maximal capacity, and no node gets overloaded at any time.

  • Cost efficiency

    Compliant with customers’ expectations. OpenIO reduces cost and TCO by 80% compared with legacy storage arrays, without compromising on data protection or availability.

The most flexible object storage on the market

  • Innovative scale-out design

    A grid of nodes, instead of traditional cluster layouts, creates a flexible, resource conscious design capable of supporting heterogeneous hardware.

    Clusters can contain any type of node, which allows different hardware generations and capacities to be combined over time without affecting performance and efficiency.

  • Hardware agnostic

    fully software-defined solution that runs on x86 and ARM with minimal requirements. Supported in mixed physical and virtual environments as well as deployed in containers, the cloud, or at the edge.

    Freedom of choice and cost savings for any type of deployment.

  • Event-driven

    OpenIO collects all events that occur in the cluster and can pass them up in the stack or directly to an application on the local node. OpenIO’s Grid for Apps serverless framework takes advantage of all OpenIO features and can process all events seamlessly, integrating third-party frameworks as well.

    An application backend for micro services, automated data processing workflows, and event-driven applications.

  • Multitenancy by design

    The cluster can have multiple domains as well as accounts and containers. Data can be organized in different storage pools and protection schemes.

    Segregate workloads and improve overall system efficiency.

  • Dynamic placement policies

    Thanks to Conscience technology, each operation is performed on the most available node. Each node of the cluster computes a quality score every few seconds and shares it on a distributed shared board accessible to all nodes.

    Each time a new operation is requested, the best nodes are selected for optimal resource utilization, continuous system tuning, and enforcement of customers’ fine-grained constraints.

  • No rebalancing

    Conscience technology eliminates the need for cluster rebalancing. When new nodes are added, they use a scoring mechanism to progressively offload the nodes already in place. And as the most recent nodes have a better quality score than older, heavy-loaded nodes, they’ll be used more often.

    These new resources are immediately available and guarantee improved performance.

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