Double booking is one of the most important problems in any reservation system. Two users may see the same seat as available and submit their requests almost at the same time. A simple availability check is not enough when requests run concurrently.
Why the basic check fails
Imagine that request A checks seat 12 and finds no reservation. Before it saves, request B performs the same check and gets the same result. Both requests then create a reservation. The application logic looked correct, but the operations were not protected as one unit.
Protect the rule in the database
The strongest solution is to enforce uniqueness at the database level. Depending on the model, a unique constraint can cover the seat and time slot, or the seat and reservation date. Even if two application threads race, the database will reject the second conflicting record.
Use transactions deliberately
The service method that checks availability and creates the reservation should run inside a transaction. For more complex time ranges, pessimistic locking can lock the relevant seat while the decision is made. Optimistic locking is useful when conflicts are uncommon and retrying is acceptable.
Return a useful conflict response
A rejected booking is an expected business outcome, not an unknown server failure. Convert the conflict into HTTP 409 and explain that the requested seat or period is no longer available. This gives the client a chance to refresh availability and offer alternatives.
Test concurrent requests
Unit tests alone may miss race conditions. Add an integration test that sends competing booking requests and verifies that only one reservation is stored. Reliability comes from combining service rules, transaction boundaries, database constraints, and realistic tests.