Optimize Transaction Throughput: 3 Patterns for Scaling with Convex and ACID Databases

The text discusses strategies for optimizing transaction throughput in ACID databases, using Convex as an example but applicable to any database employing optimistic concurrency control. It introduces three patterns: "Queue," "Hot and Cold Tables," and "Predicate Locking," each designed to minimize conflicts and increase concurrency. The "Queue" pattern involves processing data batches to reduce conflicts by separating read and write operations, while the "Hot and Cold Tables" pattern suggests splitting database fields based on their update frequency to prevent conflicts. The "Predicate Locking" pattern enables parallel operations by creating compound indexes to only query documents that meet specific conditions, thus avoiding unnecessary conflicts. These patterns aim to help databases scale efficiently by reducing transaction conflicts and improving throughput.

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