file storage vs object storage

In a file storage service. example services: Elastic File System and google file store DataStructure: - Data is stored in a hierarchical structure (folders and files), similar to how data is organized in traditional file systems. - Uses the NFS protocol, making it accessible from other compatible environments. Access and Use Case

• EFS can be used when you need shared access to a file system across multiple EC2 instances or when applications require standard file system access (like mounting directories).
  • Use Cases: Web serving, content management, file sharing, home directories, etc.
  • It’s ideal for POSIX-compliant workloads, which require file system semantics (like permissions and file locks). Scalability:
• file storage like EFS is automatically scalable and adjusts to the size of your data. It provides high availability and can scale up to petabytes of data.
  • Designed for low-latency access to a shared file system. Access Method file storage like EFS can be mounted directly onto EC2 instances as a file system using standard file system commands like mount. It can also be accessed from on-premises environments through AWS Direct Connect or VPN.

Performance

• EFS offers high throughput and low-latency performance for use cases requiring frequent read/write access to files. It supports concurrent access from thousands of EC2 instances.

In an object storage service. DataStructure:

• Data is stored as objects within buckets. Each object consists of data, metadata, and a unique identifier.
• There is no file hierarchy in S3. Files are organized by object keys (which can look like a folder structure but isn’t a true hierarchy).
• example services: S3 and Google Cloud object storage Access and Use Case
• S3 is used for storing large volumes of data and can be accessed over the internet via HTTP/HTTPS or programmatically through APIs.
  • Use Cases: Backup and archival, data lakes, media storage, big data analytics, and cloud-native applications.
  • It’s ideal for storing unstructured data such as logs, backups, images, or videos.
    Scalability:
• object storage like S3 is highly scalable as well but in terms of object storage. You can store unlimited amounts of data across many geographic regions. It is designed for storing massive amounts of data that need to be accessed with higher latency and lower throughput compared to file storage systems.

Access Methods:

• object storage like S3 is accessed through APIs, SDKs, or via HTTP/HTTPS. Files are accessed by unique object keys instead of file paths, which gives more flexibility but less traditional file system behavior. Performance
• S3 has higher latency compared to file systems but can handle very high-throughput workloads with infrequent access patterns, particularly for large objects.
  • Great for bulk storage but not for workloads requiring rapid, frequent updates to files.