Simulate how different PartitionKey strategies affect data distribution, throughput, and query performance in Azure Table Storage. Choose a strategy, configure your workload, and see the impact visually.
⚙️ Configuration
100,000
📊 Results Summary
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Total Partitions
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Max Entities / Partition
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Avg Entities / Partition
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Peak Ops / Partition / sec
📈 Partition Distribution
Entity count per partition (top 50 shown if many partitions)
🌡️ Throughput Heatmap
Estimated operations/sec load per partition
💡 Recommendations
📚 How Partition Strategy Affects Performance
Azure Table Storage Partition Limits:
• Each partition can handle up to 2,000 entities/sec throughput
• Entity Group Transactions (batch) limited to 100 entities in same partition
• Single entity max size: 1 MB; single partition: effectively unlimited rows
• Table-level target: 20,000 ops/sec per storage account
• Each partition can handle up to 2,000 entities/sec throughput
• Entity Group Transactions (batch) limited to 100 entities in same partition
• Single entity max size: 1 MB; single partition: effectively unlimited rows
• Table-level target: 20,000 ops/sec per storage account
| Strategy | Best For | Watch Out |
|---|---|---|
| Date-based (day) | Time-series, logs with date queries | Today's partition = hot spot |
| Category-based | Few, well-defined groups; batch ops | Uneven category sizes → hot partitions |
| Unique (GUID) | Max parallelism, point queries | No batch ops, no range scans |
| Composite | Balances grouping with distribution | More complex key management |
| Hash-bucket | Write-heavy, even distribution needed | Loses natural ordering; fan-out reads |