Provisioned capacity mode is appropriate for workloads with consistent or predictable throughput. However, when write capacity is significantly over-provisioned relative to actual usage, it results in wasted spend. This inefficiency is especially common in dev/test environments, legacy systems, or workloads that have tapered off over time but were never adjusted.

Provisioned capacity mode is appropriate for workloads with consistent or predictable throughput. However, when read capacity is significantly over-provisioned relative to actual usage, it results in wasted spend. This inefficiency is especially common in dev/test environments, legacy systems, or workloads that have tapered off over time but were never adjusted.

This inefficiency occurs when a table remains in the default Standard storage class despite having minimal or infrequent access. In these cases, switching to Standard-IA can significantly reduce monthly storage costs, especially for archival tables, compliance data, or legacy systems that are still retained but rarely queried.

This inefficiency occurs when a DynamoDB table is no longer accessed by any active workload but continues to accumulate storage charges. These tables often remain after a project ends, a feature is retired, or data is migrated elsewhere. Without any read or write activity, the table provides no functional value and becomes a cost liability.

While On-Demand mode is well-suited for unpredictable or bursty workloads, it is often cost-inefficient for applications with consistent throughput. In these cases, shifting to Provisioned mode with Auto Scaling allows teams to set a baseline level of capacity and scale incrementally as needed—often yielding substantial cost savings without compromising performance.