For developers, architects, and technical leads deciding how to store data in their applications.
Three Storage Types, Three Different Problems
Storage is not a single category. Object storage, block storage, and file storage each emerged to solve different access patterns, at different scales, with different tradeoffs. Using any one of them for the wrong workload does not just create technical debt — it creates cost problems, performance problems, and architectural rigidity that compounds as the application grows.
Understanding the difference is not academic. It is the foundation of a storage architecture that scales correctly.
Block Storage — The Raw Disk Abstraction
Block storage presents itself to the operating system as a raw disk. It does not know about files, directories, or objects. It knows about blocks — fixed-size chunks of data that the OS or application reads and writes by block address. The file system sits above the block storage layer and imposes structure on top.
How it works: Your application writes data through the OS file system, which writes to block addresses on the block storage volume. The storage layer has no awareness of what the data means — it just stores and retrieves blocks.
What it is good for: Databases, operating system volumes, and any workload that requires low-latency random read/write access to structured data. A PostgreSQL database on an EBS volume, a MySQL instance on a block storage volume — block storage is what makes databases fast, because random seeks to specific block addresses are fast.
What it is not good for: Storing large numbers of files, sharing data across multiple servers simultaneously, or storing unstructured data like media files. Block storage volumes are typically attached to a single server. They do not scale horizontally without significant architecture work.
Where you will encounter it: AWS EBS, Azure Managed Disks, GCP Persistent Disk, IBEE block storage volumes. Every cloud virtual machine's root disk is block storage.
File Storage — The Shared Directory Abstraction
File storage presents a familiar directory tree interface — folders, files, paths. Unlike block storage, file storage can be accessed by multiple clients simultaneously over a network protocol (NFS, SMB/CIFS, AFP). It is what most people think of when they think of a server with files on it.
How it works: The storage system manages a file system with directories and files. Clients mount the storage over a network and interact with it using standard file operations — open, read, write, close, list directory, delete. The storage system handles concurrency, locking, and consistency across multiple clients.
What it is good for: Shared file systems where multiple servers need to read and write the same files, legacy applications designed around POSIX file system semantics, content management systems that expect a local directory structure, and workflow tools that process files sequentially.
What it is not good for: Storing billions of files, internet-scale distribution of files to end users, or workloads that need to scale across data centres and regions. File storage systems face significant challenges at extreme scale.
Where you will encounter it: AWS EFS, Azure Files, NFS shares on-premise. A shared code repository mounted across multiple application servers is file storage. A CMS with a media uploads directory mounted across a cluster is file storage.
Object Storage — The Web-Scale Unstructured Data Layer
Object storage replaces the file/directory metaphor with a flat namespace of objects. An object is a blob of data — any data, any size, any format — plus a key and a set of metadata. You store objects by key and retrieve them by key. There are no directories, no locking, no concept of random writes to the middle of an object.
How it works: You PUT an object to a bucket with a key. You GET the object back by key. You LIST objects in a bucket, optionally filtered by key prefix. You DELETE objects by key. The HTTP-based API means any language, any platform, any network-connected client can interact with object storage without a special protocol or mount point.
What it is good for: Storing and serving large volumes of unstructured data — images, videos, audio files, documents, backups, log archives, ML datasets, static web assets. Object storage is designed to scale to billions of objects at petabyte scale, serve them at high throughput to many concurrent clients, and do so at a cost that reflects the economics of bulk storage rather than high-performance local disk.
What it is not good for: Workloads that need POSIX file semantics — you cannot append to the middle of an object, you cannot list a true directory tree, you cannot set file permissions the way a Unix file system does. Databases do not run directly on object storage. Applications that expect to seek within a large file at arbitrary byte offsets will find object storage's whole-object read model limiting.
Where you will encounter it: AWS S3, IBEE, Google Cloud Storage, Azure Blob Storage. Every image CDN, every video streaming platform, every backup system, every static website — these all run on object storage.
The S3 API as the Universal Interface
AWS S3 defined the dominant object storage API — a set of HTTP operations (PUT, GET, DELETE, LIST, COPY, HEAD, multipart upload) that became the de facto standard for cloud object storage. The S3 API is now implemented by dozens of storage providers, including IBEE.
Full S3 compatibility means any application, SDK, CLI tool, or infrastructure component built for AWS S3 works with IBEE by changing the endpoint URL and credentials. This is why S3 compatibility matters as a feature — it determines whether you can switch providers without rewriting application code.
Choosing the Right Storage Type
For a given data storage requirement, the decision typically follows this logic:
If the data needs to be read and written with low-latency random access by a database or OS — block storage is correct. Run your PostgreSQL instance on a block storage volume, not on an NFS share, and certainly not by writing database files to object storage.
If the data needs to be shared across multiple servers simultaneously with file semantics — shared file storage is correct. A rendering farm where multiple nodes write output frames to a shared directory, a CMS whose media upload directory must be accessible across all application servers — these are file storage use cases.
If the data is a collection of discrete objects that need to be stored at scale, retrieved over HTTP, served to end users or downstream systems, or archived for long retention — object storage is correct. User-uploaded files, media libraries, static website assets, ML training datasets, database backups, log archives — all of these belong in object storage.
Why Most Modern Application Data Belongs in Object Storage
The vast majority of data that web and mobile applications generate is unstructured and discrete — images uploaded by users, documents generated by the application, audio recordings, video files, reports, exports. None of this benefits from the POSIX semantics of file storage or the block-level access of disk storage. All of it benefits from object storage's scale, cost efficiency, HTTP accessibility, and durability characteristics.
An application that stores user profile photos on a local disk attached to the application server has made a mistake that will require a migration when the server runs out of disk space, when a second application server is added, or when the server is replaced. The same data in an object storage bucket scales indefinitely, is accessible from every server, and survives any individual server failure.
IBEE Object Storage for Indian Applications
IBEE's S3-compatible object storage is designed for Indian application workloads — storage at Rs.1.50/GB-month, egress at Rs.2/GB for Indian users, Tier 4 reliability, and sub-5ms latency from Indian infrastructure. For applications serving Indian users where data currently lives on attached server disks or shared NFS mounts, the migration to object storage is typically a day's work — and the architectural improvement is permanent.
