Announcement
Apache Ozone: Scalable Distributed Object Storage for Big Data
Apache Ozone is a highly scalable, reliable, and distributed object store designed for large-scale data analytics, machine learning, and containerized applications. It provides a robust and efficient storage solution for modern workloads.
Project Introduction
Summary
Apache Ozone is a distributed object storage system built for scalability and reliability in big data and cloud-native environments. It provides a robust alternative to traditional file systems for object-based workloads and data lakes.
Problem Solved
Traditional distributed file systems like HDFS can struggle with the massive scale, metadata overhead, and object storage requirements of modern data analytics and cloud-native workloads. Ozone provides a specialized, scalable object store solution.
Core Features
Massive Scalability
Designed to scale to billions of objects and petabytes of data across large clusters.
S3 Compatibility
Offers an S3-compatible API for seamless integration with existing cloud-native applications and tools.
High Reliability
Ensures data durability and availability through configurable replication strategies and fault tolerance.
Tech Stack
使用场景
Apache Ozone is suitable for a variety of use cases requiring scalable and reliable object storage, including:
Large-scale Data Lakes
Details
Use Ozone as the foundation for a data lake, storing raw and processed data for engines like Apache Spark, Hive, and Presto.
User Value
Provides a highly scalable, performant, and cost-effective storage layer for petabyte-scale analytics.
Object Storage for Cloud-Native Applications
Details
Serve as the primary object storage backend for applications deployed on Kubernetes, offering S3-compatible access for seamless integration.
User Value
Enables easy integration of scalable storage into containerized microservices and applications.
AI/ML Data Repository
Details
Store vast datasets, models, and results for machine learning training, inference, and data science workflows.
User Value
Offers reliable and efficient storage for demanding AI/ML workloads.
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