Understanding Soft Deletion

The data produced by software applications holds significant value, including information that may eventually be discarded. Retaining deleted data can be beneficial for tracking historical changes, identifying trends, and examining data relationships. Moreover, certain application components can leverage this historical information.

Consequently, many applications are structured so that data is never fully removed. A common technique used for this purpose is Soft Deletion. While this method seems straightforward, it can introduce various complications. In this discussion, we will explore the intricacies of Soft Deletion, as well as an alternative method and its respective advantages and disadvantages.

Advantages of Soft Deletion

The primary benefit of Soft Deletion is the ease of restoring deleted data. Recovery is as simple as toggling the flag field. Additionally, this method tends to be quicker than hard deletion, as database UPDATE operations are generally more efficient than DELETE operations.

Soft Deletion also proves invaluable during debugging. The flexibility it offers allows for easier analysis of production data when everything resides in a single table or collection.

Challenges of Soft Deletion

Despite its advantages, Soft Deletion presents some complexities that can be cumbersome to manage.

Firstly, all application queries must include a condition to exclude deleted records. Neglecting this filter can lead to unintended exposure of deleted data. A typical query would look like this:

SELECT * FROM users WHERE deleted=false;

While it may seem trivial at first, forgetting this condition is common, especially in large codebases with complex queries involving multiple joins.

Creating database views that apply this condition can be an effective workaround. However, as deleted records accumulate, SELECT operations may slow down. Single-column indices will not suffice, as every query must filter using the deleted flag.

Implementing a multi-column index, starting with the deleted flag field, can enhance query performance. For instance:

CREATE INDEX "users_username_unique" ON users(deleted, username);

If there are numerous deleted records, this index will significantly reduce the search space when filtering by both deleted status and username:

SELECT * FROM users WHERE deleted=false AND username="foobar";

Similar multi-column indices can be established for other fields. Nevertheless, these indices may slow down UPDATE operations due to the overhead associated with maintaining them.

Database constraints can also complicate matters in a Soft Deletion scenario. For example, consider a unique constraint on the email field in the users table. If a user with the email [email protected] deletes their account and later tries to create a new one with the same email, a conflict arises.

To address this, a partial index is necessary, which allows indexing on a subset of records using a WHERE clause:

CREATE UNIQUE INDEX "users_username_unique" ON users(deleted, email) WHERE deleted=false;

This ensures that unique indexing applies only to active records, ignoring duplicates in deleted ones. However, partial indices are not universally supported and may also slow down UPDATE operations.

It's also crucial to remember that while the flag field may tempt developers to simply mark records as deleted, sensitive data must be handled differently. Here's an example of how to manage sensitive information:

UPDATE users SET deleted=true, deleted_date=NOW(), credit_card_number=NULL WHERE id='someId';

An Alternative: Hard Deletion with Archiving

Next, let’s consider an alternative to Soft Deletion—Hard Deletion with Archiving. In this method, records are copied to an archive table prior to deletion, effectively storing deleted data for future reference.

Implementing this can be straightforward using a database trigger. For example, in PostgreSQL:

CREATE TRIGGER archive_user_before_delete

BEFORE DELETE ON users

FOR EACH ROW

EXECUTE PROCEDURE archive_user();

Advantages of Hard Deletion with Archiving

The main advantage of this approach is the clear separation between active and deleted data, eliminating the risk of exposing deleted records. Furthermore, it allows for selective archiving of only relevant fields, ensuring sensitive information is removed and minimizing storage requirements.

Additionally, from a database perspective, there is no need to create complex indices due to the deleted flag.

Drawbacks of Hard Deletion with Archiving

Although this approach offers clear benefits, it is not without its drawbacks. Restoring deleted data becomes more complicated, as it requires moving records from the archive table back to the original table. However, a robust database setup should include regular backups, which can aid in data recovery. Furthermore, restoring deleted records is usually a rare occurrence, making the additional time acceptable.

Another downside is that DELETE operations tend to be slower than UPDATE operations. The added time for triggering and inserting data into the archive can be a concern. However, in tables where soft deletion is not an option, using DELETE commands should not pose significant issues, as it ensures indices only contain live data.

Maintaining relationships on archived tables can also be challenging. For instance, if the users table has a many-to-one relationship with a companies table, the company referenced in a record in users_archive might exist in either the companies table (for active companies) or companies_archive (for deleted ones).

Conclusion

While Soft Deletion is simpler to implement, it carries some technical challenges that developers should consider when working with related tables and collections. It may also lead to performance issues due to the complexity of indices. Nonetheless, it provides advantages such as easy restoration and the ability to maintain relationships with deleted data.

On the other hand, Hard Deletion with Archiving requires more setup—using triggers and extra tables—but simplifies query management and ensures clean indices, making it easier to identify performance issues. This approach prioritizes the separation of concerns over some of the convenience features of Soft Deletion.

Ultimately, the choice between these two methods depends on the specific needs of the application and the practices of the development team. Each approach has its unique set of pros and cons, and it may be prudent to opt for Soft Deletion only if business requirements explicitly call for it.