Relational databases store binary data using a specialized data type called BLOB, which stands for Binary Large Object. BLOBs are designed to hold large amounts of binary data, such as images, audio files, or other multimedia content. When you create a database table, you can define a column as a BLOB type to accommodate this kind of data. This storage method allows the database to handle large files efficiently while still maintaining the structural integrity of the relational model, which keeps the data organized and accessible through familiar SQL queries.
In practical terms, when you insert binary data into a BLOB column, the database system manages the data in a way that optimizes storage and access. Instead of trying to fit the entire binary file into memory, the database streams the data in chunks, storing it in a way that reduces performance overhead. For example, if you need to insert an image into your database, you can read the image file as a byte array and use an SQL statement to insert that byte array into the BLOB column. This way, you can keep the actual image file outside of your application's file structure while still being able to retrieve it whenever needed.
Accessing binary data in a BLOB field typically requires additional programming support but follows a straightforward pattern. You can retrieve the binary data using a SELECT statement and then convert it back into a usable format within your application. Likewise, when updating or deleting binary data in BLOB fields, the same SQL commands apply, but you need to handle the byte streams correctly. For example, if you want to replace an existing file with a new version, you would read the new file's binary data and execute an UPDATE statement to modify the existing BLOB. Overall, BLOBs provide a powerful way to manage and store binary data effectively within relational databases.