A Cloud Native Unstructured Data Storage

CubeFS is a new generation cloud-native storage that supports access protocols such as S3, HDFS, and POSIX. It is widely applicable in various scenarios such as big data, AI/LLMs, container platforms, separation of storage and computing for databases and middleware, data sharing and protection,etc.

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The Key Features of CubeFS


Compatible with various access protocols such as S3, POSIX, HDFS, etc., and the access between protocols can be interoperable


Support replicas and erasure coding engines, users can choose flexibly according to business scenarios

Highly Scalable

Easy to build a PB or EB-scale distributed storage service, and each module can be expanded horizontally


Supports multi-tenant management and provides fine-grained tenant isolation policies

High Performance

Supports multi-level caching, multiple high-performance replication protocols, and optimizes specific performance for small files


Easy to use CubeFS in Kubernetes via CSI Driver

CubeFS Deployment

CubeFS has developed a CSI plugin based on the Container Storage Interface (CSI) interface specification to support cloud storage in Kubernetes clusters.

CubeFS Application Scenarios

CubeFS is a cloud-native storage infrastructure that is widely used in a variety of scenarios, including big data storage, machine learning platforms, large-scale container platforms, as well as database and middleware storage and computing separation. It is also used for data sharing and protection.

Building a Highly Reliable, Highly Available, Low-Cost, and EB-Scale Independent Key-Value Storage System with CubeFS.

As data continues to grow, businesses face greater cost challenges. In order to alleviate the storage cost pressure caused by multi-copy mode, CubeFS has introduced a erasure code subsystem (also known as BlobStore), which is a highly reliable, highly available, low-cost, and EB-scale independent key-value storage system.

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Co-creating the Future with CubeFS: BIGO's Practice and Reflection

With the growth of the BIGO machine learning platform's models and data, more demands are placed on the underlying file system, such as multi-tenancy, high concurrency, high availability across multiple datacenters, high performance, and cloud-native features. CubeFS effectively meets these requirements, and BIGO is attempting to use CubeFS to address these challenges.

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Data Lake Unified Storage Technology Practice

OPPO has been storing its large-scale data in HDFS clusters with a total storage capacity of EB-level. However, due to the rapidly growing business, the company faced several operational issues, including lack of machine resources, high operational costs, and high redundancy in storing cold and hot data. In order to solve these problems, OPPO implemented CubeFS

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How CubeFS Accelerates AI training 3x in OPPO Hybrid Cloud platform

The article discusses OPPO's machine learning platform which supports over 100 AI businesses with tens of thousands of daily training tasks. In 2021, AI pioneers Oppo built a large-scale, end-to-end machine learning platform, leveraging CubeFS, to support AI training for more than 100 Oppo businesses – running tens of thousands of training tasks every day for business fields including voice assistant, commercial advertisement, OPPO game, ctag multi-mode, NLP and more.

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Trusted by the Advanced Technology Enterprises

A young dynamic architecture firm, CubeFS provides peace of mind to any developer or homeowner dedicated to excellence.

Latest Blog

CubeFS completes third-party security audit


CubeFS is happy to announce the completion of its third-party security audit. The audit was conducted by Ada Logics in collaboration with the CubeFS maintainers, OSTIF and the CNCF.

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Application practice of Raft in CubeFS erasure code system


The given text describes the CubeFS erasure coding service’s metadata management module (Blobstore/ClusterMgr), Raft algorithm practice, and daily operation recommendations.

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Secret of CubeFS| Multi-AZ Erasure Coding Disaster Tolerance


This article introduces the AZ-level disaster tolerance scheme of the Blobstore erasure coding subsystem in CubeFS. Due to the disadvantages of high storage cost and low efficiency in the multi-replica storage mode, high network bandwidth consumption in the multi-AZ case, and the need to ensure data consistency in a timely manner, we will only discuss the erasure coding (EC) storage mode. Blobstore uses erasure coding to encode and calculate user data and persistently store it in multiple AZs, achieving high availability and disaster tolerance. The main content of the article includes the EC calculation principle in multiple AZs, as well as how to maintain high availability for writing, efficient reading, and reducing cross-AZ data recovery. The reliability for EC data is not elaborated here, and can be found in our related articles.

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