Storage throttling only surfaces at production scale. These simulators let you visualize partition behaviour and detect hot-spots before you deploy — no Azure account needed.
Table Storage gives you explicit control over the PartitionKey — making it the most impactful design decision. Simulate date-based, category-based, unique, composite, and hash-bucket strategies.
Blob partitioning is driven by naming patterns. Sequential names are the #1 anti-pattern. Simulate how different naming conventions (hash-prefix, GUID, timestamp) affect partition distribution.
Azure Files performance is driven by share size, tier, and protocol rather than naming. Simulate IOPS, throughput, and capacity against provisioned limits across shares.
| If you need… | Start with… |
|---|---|
| High-throughput structured data, batch operations | Table Storage — PartitionKey design is critical |
| Large-scale blob ingestion (IoT, logs, media) | Blob Storage — naming pattern determines scale |
| Shared file system (SMB/NFS lift-and-shift) | Azure Files — tier and share sizing are key |