BLOB: Binary Large Object
- DB has acid properties
- DB indexing can provide better search and retrieval capabilitites
- Mutability: BLOB storage allows for easy updates and changes to image data.
Cons:
- Overhead for Immutable Data: When images are mostly immutable (only a few bytes change when updated), the overhead of storing them in a database may not be cost-effective
- Performance for Read-Heavy Workloads: Retrieving images from a database can be slower for read-heavy workloads, especially when serving images to a large number of users
File Storage in a Distributed File System, e.g Hadoop HDFS or Amazon S3
- Scalability: Distributed file systems are highly scalable and can handle massive volumes of image data.
- Cost-Effective: They are often more cost-effective, particularly for applications with dynamic scaling requirements and pay-as-you-go pricing.
- Parallel Processing: Distributed file systems, like HDFS, are designed for parallel processing, making them suitable for image analysis and processing.
- Data Replication (HDFS): In HDFS, data replication ensures fault tolerance, reducing the risk of data loss due to hardware failures. Cons: No indexing No ACID properties No fine grain access control
By combining database storage for metadata and a distributed file system for actual image files, you strike a balance between data consistency, performance, and cost-efficiency, making it a practical solution for many image storage scenarios.