What Consistency Really Means in Data Systems?

“Can your system achieve strong consistency?” As practitioner who has been developing stream processing systems over the last few years, I encounter this question frequently. I'm often tempted to confidently promote our product, but realistically, answering this query is complex. The challenge lies not in the question itself but in the fact that "consistency" means different things to different people depending on their technical background.

each have their own interpretation of consistency. Answering without contextual understanding can lead to misunderstandings. In this article, I will clarify what consistency actually means across these different data systems.

In traditional databases, consistency is a cornerstone among the ACID properties (Atomicity, Consistency, Isolation, Durability). This principle guarantees that each transaction transitions the database from one valid state to another. For instance, in a banking transaction where one account is debited and another credited, consistency ensures the aggregate balance remains unchanged. It's crucial to distinguish this from atomicity, which refers to the all-or-nothing nature of transactions. For example, atomicity ensures that all operations within a transaction are completed successfully, or none at all, ensuring no partial transactions are ever left in the database.

In summary, database consistency focuses on enforcing rules that preserve data correctness and validity throughout transactions.

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