Deduplicating Data in System Design
A user uploads the same 50MB video five times because their network kept dropping. Your storage costs just quintupled for a single file.
A message queue retries a failed message. The consumer processes it again. Now there are two charges on the customer's credit card.
A distributed system syncs data across nodes. The same record arrives from three different sources. Your database now has three copies of "truth."
These scenarios share the same root cause: duplicate data. In distributed systems, duplicates are not a bug to be fixed, they are a fundamental reality to be managed. Networks drop packets. Services retry requests. Users double-click submit buttons.
The only question is whether your system handles duplicates gracefully or lets them cause real damage.
This chapter covers how to detect and eliminate duplicates across different scenarios: file storage, message processing, database records, and API requests. You will learn six battle-tested strategies that show up repeatedly in production systems and system design interviews alike.