How do relational databases store binary data?

Relational databases store binary data using specialized column types designed to handle raw byte streams. Common data types include BLOB (Binary Large Object) in MySQL, BYTEA in PostgreSQL, and VARBINARY in SQL Server. These columns store binary data as-is, without interpretation or encoding, making them suitable for files like images, PDFs, or serialized objects. When inserting data, applications typically convert files or binary streams into byte arrays and bind them to database parameters. Retrieval involves reversing this process, converting the stored bytes back into usable formats. This approach ensures the database treats binary data as opaque values, preserving their integrity.

Storage mechanics vary by database. For example, MySQL’s BLOB types (e.g., TINYBLOB, LONGBLOB) support sizes from 255 bytes to 4GB. PostgreSQL’s BYTEA stores binary data directly, while large values are compressed and split using its TOAST (The Oversized-Attribute Storage Technique) mechanism. Some databases allow binary data to be stored inline within tables or externally in dedicated filesystems, with trade-offs: inline storage simplifies transactions and backups but can impact performance for large files. Developers often balance this by storing small binaries (e.g., user avatars) directly in the database and larger files (e.g., videos) externally, referencing them via file paths in the database.

Best practices include limiting binary storage to scenarios requiring transactional consistency (e.g., audit logs) or secure access control. For performance, avoid querying large binaries frequently; instead, use caching or CDNs. Security is critical: validate incoming data to prevent malicious uploads and use parameterized queries to avoid injection risks. Indexing binary data isn’t typically useful, but metadata columns (e.g., file type, size) can improve query efficiency. For example, a user profile table might store a BYTEA column for avatar images alongside VARCHAR fields for filenames and MIME types, enabling efficient filtering without scanning binary content.