In system design, BLOBs (Binary Large Objects) are unstructured data like images, videos, and PDFs that don't fit neatly into database rows. Unlike traditional data types, BLOBs are just seen as massive chunks of bytes by the database engine. This makes handling them a unique challenge in software development.

When storing large files, developers often face the decision between keeping them in a SQL database or using object storage services like Amazon S3. Storing BLOBs directly in a database, such as using MySQL's `VARBINARY` or PostgreSQL's `BYTEA`, offers ACID compliance and easy backups. However, it can lead to performance issues and higher costs due to expensive block storage.

The industry standard increasingly favors object storage for BLOBs. Services like Amazon S3, Google Cloud Storage, and Azure Blob provide infinite scalability, cheaper storage, and built-in redundancy. The architecture pattern for handling BLOBs involves decoupling metadata from storage, where the actual file is stored in object storage, and only a reference URL is kept in the database.

For most use cases, especially with user uploads, object storage is the preferred method. It simplifies scaling and reduces costs, making it a practical choice for modern applications. Only in specific scenarios, such as handling sensitive transactional data, do databases remain the better option.