Block storage vs object storage vs file storage in HLD - Scaling Approaches Compared

Scalability Analysis - Block storage vs object storage vs file storage

Growth Table: Block, Object, and File Storage

Scale	Block Storage	Object Storage	File Storage
100 users	Simple SAN or local disks; low latency; easy management	Basic object store; metadata overhead minimal; good for backups	Single NAS device; shared file access; simple permissions
10,000 users	Multiple SAN devices; need for volume management; IOPS start to matter	Distributed object store; metadata grows; eventual consistency considered	Clustered NAS; file locking and concurrency challenges appear
1,000,000 users	Storage area network scaling limits; expensive hardware; complex management	Highly scalable object storage clusters; metadata indexing and search critical	Distributed file systems (e.g., Lustre, GlusterFS); performance bottlenecks in metadata servers
100,000,000 users	Rare at this scale; cost and complexity very high; mostly replaced by object storage	Massive object storage with multi-region replication; strong metadata services; optimized for cloud	Very large distributed file systems; metadata and locking become major bottlenecks; complex caching needed

First Bottleneck

At small to medium scale, block storage bottlenecks appear in IOPS and volume management as the number of users and data grow.

For file storage, metadata servers and file locking cause bottlenecks as concurrency increases.

Object storage first bottleneck is metadata service scalability and network bandwidth due to large object counts and replication.

Scaling Solutions

• Block Storage: Use faster SSDs, add more volumes, implement volume striping, and scale horizontally with storage arrays.
• File Storage: Deploy distributed file systems with metadata server clustering, caching, and partitioning to reduce locking contention.
• Object Storage: Scale metadata services horizontally, use consistent hashing for data distribution, implement multi-region replication, and leverage CDNs for content delivery.

Cost Analysis (Back-of-Envelope)

• At 1M users, assuming 10 requests/user/day, total requests = 10M/day ≈ 115 QPS.
• Block storage IOPS needed can reach tens of thousands; SSDs or NVMe required.
• Object storage metadata operations can reach hundreds of thousands QPS; requires distributed metadata services.
• File storage metadata servers may need to handle thousands of concurrent locks and operations.
• Network bandwidth: For 1PB data with 10% daily churn, need ~9 Gbps sustained bandwidth for replication and access.

Interview Tip

Start by defining each storage type simply. Then discuss typical use cases and scaling challenges. Identify bottlenecks by scale and propose targeted solutions. Use real numbers to show understanding of limits and costs.

Self Check

Your database handles 1000 QPS. Traffic grows 10x. What do you do first?

Answer: Add read replicas and implement caching to reduce load on the primary database before considering sharding or hardware upgrades.

Key Result

Object storage scales best for massive data and users due to its distributed metadata and replication design; block storage is limited by hardware IOPS and volume management; file storage faces metadata and locking bottlenecks at scale.

Practice

1. Which storage type splits data into fixed-size blocks and provides fast, low-level access?

easy

A. Block storage

B. Object storage

C. File storage

D. Cloud storage

Solution

1. Step 1: Understand block storage concept

   Block storage divides data into blocks and stores them separately for quick access.

2. Step 2: Compare with other storage types

   Object storage stores data as objects with metadata, and file storage organizes data in files and folders.

3. Final Answer:

   Block storage -> Option A

4. Quick Check:

   Block storage = fast block-level access [OK]

Hint: Blocks mean fast raw data access, not files or objects [OK]

Common Mistakes:

• Confusing object storage with block storage
• Thinking file storage splits data into blocks
• Assuming cloud storage is a type here

2. Which of the following correctly describes object storage?

easy

A. Stores data as blocks without metadata

B. Stores data as objects with metadata for easy retrieval

C. Organizes data in hierarchical files and folders

D. Splits data into fixed-size chunks for fast access

Solution

1. Step 1: Recall object storage features

   Object storage saves data as objects, each with metadata describing the data.

2. Step 2: Eliminate incorrect options

   Blocks without metadata describe block storage; hierarchical files describe file storage.

3. Final Answer:

   Stores data as objects with metadata for easy retrieval -> Option B

4. Quick Check:

   Object storage = objects + metadata [OK]

Hint: Objects always have metadata; blocks do not [OK]

Common Mistakes:

• Mixing block storage with object storage
• Thinking file storage uses metadata like objects
• Confusing hierarchical files with object storage

3. A company needs to store large amounts of unstructured data like images and videos with metadata for easy search. Which storage type fits best?

medium

A. Object storage for metadata and scalability

B. Block storage for fast raw access

C. File storage for hierarchical organization

D. Local disk storage for simplicity

Solution

1. Step 1: Analyze data type and requirements

   Unstructured data like images/videos benefit from metadata and scalability.

2. Step 2: Match storage type to needs

   Object storage supports metadata and scales well for large unstructured data sets.

3. Final Answer:

   Object storage for metadata and scalability -> Option A

4. Quick Check:

   Unstructured + metadata = Object storage [OK]

Hint: Metadata + large unstructured data = object storage [OK]

Common Mistakes:

• Choosing block storage for unstructured data
• Assuming file storage handles metadata well
• Picking local disk which lacks scalability

4. A developer tries to use file storage for a distributed app needing fast block-level access but experiences slow performance. What is the likely cause?

medium

A. File storage does not support hierarchical folders

B. Block storage cannot be used in distributed apps

C. File storage is not optimized for block-level raw access

D. Object storage lacks metadata support

Solution

1. Step 1: Understand file storage characteristics

   File storage organizes data in files and folders, optimized for sharing, not raw block access.

2. Step 2: Identify mismatch with app needs

   Fast block-level access requires block storage, not file storage, causing slow performance.

3. Final Answer:

   File storage is not optimized for block-level raw access -> Option C

4. Quick Check:

   File storage ≠ fast block access [OK]

Hint: File storage is for files, not fast block access [OK]

Common Mistakes:

• Believing block storage can't be used distributed
• Confusing object storage metadata with file storage
• Thinking file storage lacks folders

5. You are designing a scalable photo-sharing app. Users upload photos with tags and descriptions. Which storage type should you choose and why?

hard

A. Local disk storage, for simplicity and speed

B. File storage, to organize photos in folders by user

C. Block storage, for fast access to photo bytes

D. Object storage, to store photos with metadata and scale easily

Solution

1. Step 1: Analyze app requirements

   The app needs to store photos with tags/descriptions (metadata) and scale for many users.

2. Step 2: Match storage type to requirements

   Object storage supports metadata per object and scales well for large data and users.

3. Step 3: Evaluate other options

   Block storage is low-level without metadata; file storage is less scalable; local disk lacks scalability and reliability.

4. Final Answer:

   Object storage, to store photos with metadata and scale easily -> Option D

5. Quick Check:

   Photo app + metadata + scale = Object storage [OK]

Hint: Metadata + scale = object storage for apps [OK]

Common Mistakes:

• Choosing block storage ignoring metadata needs
• Assuming file storage scales well for many users
• Picking local disk for a cloud-scale app