MySQL Flexible Server costs

Tensor9 Cloud Adapter planning comparisons for azure::1.0.0::mysql::flexible, with backend choices shown together. Read how Tensor9 estimates service-adapter costs for price scope and capacity qualification, or return to additional services.

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Azure MySQL Flexible Server → Cloud SQL for MySQL

Origin API: azure::1.0.0::mysql::flexible. Target backend: google::1.0.0::cloudsql::mysql. Designed mapping. This cost model describes an intended adapter. Its estimated price does not establish a delivered or selectable backend.

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Azure MySQL Flexible Server · Primary allocated compute

Feature: Azure MySQL Flexible Server. Estimated monthly service charges by Primary allocated compute. Adapter hosting and Tensor9 fees are excluded. Source: eastus; target: us-central1; currency: USD. Comparison pills describe all sampled scale points; amounts beside each service are for the named workload. Costs The Same means within 20% at every point. Costs Depend includes mixed results and unpriced samples. Sampled monthly charges in USD, rounded to cents. Difference means target minus origin; a positive difference means the target costs more. Estimated allocation, not benchmark calibrated: sized from 2 vCPU, 8 GiB memory and 100 GiB SSD at 0 vCPU-hours/month to 64 vCPU, 256 GiB memory and 100 GiB SSD at 46,720 vCPU-hours/month. Curve assumptions

• CPU allocation does not imply an achieved transaction rate. Other native meters and workload assumptions retain their explicitly displayed default quantities. Workload translation and capacity assumptions are not benchmark measurements.
• Native monthly usage priced at the cited provider list prices; listed target allowances apply where present, excluding invoice credits, taxes and negotiated discounts. Rates as of 2026-10-22: eastus → us-central1, USD/month.
• Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
• Samples of explicit prices are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
• Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve’s workload note.
• Rates are cited provider list prices, editable for discounts, commitments or another region. Workload translation and capacity coefficients remain editable planning assumptions, not benchmark measurements or a commercial quote.
• Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
• Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
• Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
• A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
• This exact directed mapping has a design profile. Cost modeling does not establish an implemented or deployable adapter.
• Authored planning assumptions, not measured adapter capacity. Origin rates are cited first-tier list prices, before free allowances and discounts.
• A cost scenario does not establish backend availability, protocol fidelity or production readiness. Registry serving status remains independent.
• Provisioned compute and RAM are priced by resource-hour; operations are independently authored. Database size cannot be inferred from dollars alone.
• Aurora/AlloyDB, MySQL/PostgreSQL and proxied targets retain their distinct backend contracts. HA, replicas and proxy allocations must be selected explicitly.
• Flexible Server memory is included in the vCore price; the memory meter is zero so RAM is not counted twice.
• Cloud SQL Enterprise edition (MySQL) publishes separate vCPU, memory and SSD prices for zonal instances; a high-availability (regional) instance bills exactly twice each, which the standby copy reproduces. Enterprise Plus, committed-use discounts, backups (USD 0.08 per GiB-month) and idle IPv4 addresses (0.01 per hour) are not selected.
• Row-store throughput (capacityOpsPerVcpuSecond, default 1500) is measured-by-tensor9 as a lower bound: the DynamoDB adapter on Cloud SQL db-custom-2-7680 (2 vCPU, PostgreSQL 16, us-west1) served 2,974 ops/s of YCSB-A at 16 threads without recorded saturation (src/main/kotlin/t9/prime/equiv/generated/eval/CloudsqlPostgresqlYcsbAT16GoYcsbV1_0_0.kt). Published CPU-bound pgbench reaches 3,101 read-write transactions and 20,289 point reads per vCPU-second (AWS z1d.2xlarge, PostgreSQL 14.5), so actual capacity is likely higher. Reads and writes share one coefficient: at the same adapter version, read-only YCSB-C was not faster than 50%-update YCSB-A.
• Log-broker throughput (capacityStreamMiBPerVcpuSecond 20 at 0.5 utilization, 4 GiB RAM per vCPU) is provider-documented by Google Managed Service for Apache Kafka sizing (https://docs.cloud.google.com/managed-service-for-apache-kafka/docs/plan-cluster-size): write-equivalent bytes are replicated writes plus a quarter of reads. Producer batches below 10 KB lower per-CPU throughput; that penalty is not modeled.
• Disk utilization 0.8 is provider-documented headroom below Cloud SQL automatic storage increase, which triggers near 91-95% full (https://docs.cloud.google.com/sql/docs/postgres/instance-settings). The 20 GiB reserve exceeds PostgreSQL’s 1 GB default max_wal_size; the remainder of that reserve is unmeasured.
• CPU tiers double from 2 vCPUs to the target’s largest node at 4 GiB per vCPU; each target’s documented largest node bounds CPU, RAM, RAM per vCPU and disk, and the durable staging database uses Cloud SQL Enterprise (96 vCPU, 6.5 GiB per vCPU, 624 GiB, 64 TiB). Targets billed per capacity unit or throughput unit are sized by their backend instead.
• No public evidence: peak/mean work (2) and the RAM working-set fraction (0.1). Proposed measurements: the p99 one-minute rate over the monthly mean from customer CloudWatch metrics; the buffer hit ratio while stepping RAM under a fixed YCSB-B load.
• Node bounds: Cloud SQL Enterprise allows 1-96 vCPUs at 0.9-6.5 GB per vCPU and up to 64 TB with a dedicated vCPU (https://docs.cloud.google.com/sql/docs/postgres/instance-settings).
• Stored GiB already includes the origin family’s physical footprint assumptions; no second storage amplification is applied.
• The workload family already selected resource-hours; the throughput coefficient is not applied again.
• Copies and allocation fractions change cost only; they do not increase modeled primary capacity.
• Azure Retail Prices API: https://prices.azure.com/api/retail/prices
• Cloud SQL pricing: https://cloud.google.com/sql/pricing

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied. Excluded costs and workload features:

• Additional network transfer, backups, KMS, one-time migration and operational labor unless an explicit meter includes them.
• Destination application execution and separately billed downstream services; supply those allocations separately.
• Aurora per-IO, serverless-capacity, backup and proxy charges; reserved/committed-use purchase options.
• Taxes, discounts, credits and free-tier allowances not explicitly listed by this model.
• Unmodeled dependent services, task execution and operations outside the selected workload family.

List prices read: 2026-10-22. Model: plan-e57f7ffe0ebc14b9a56d6bfe1599e4ef0c1ee6f2 / 2026-10-22.planning.2. Curve: workload-1. Sources: Azure Retail Prices API, Cloud SQL pricing.

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Azure MySQL Flexible Server · Stored data

Feature: Azure MySQL Flexible Server. Estimated monthly service charges by Stored data. Adapter hosting and Tensor9 fees are excluded. Source: eastus; target: us-central1; currency: USD. Comparison pills describe all sampled scale points; amounts beside each service are for the named workload. Costs The Same means within 20% at every point. Costs Depend includes mixed results and unpriced samples. Sampled monthly charges in USD, rounded to cents. Difference means target minus origin; a positive difference means the target costs more. Estimated allocation, not benchmark calibrated: sized from 2 vCPU, 8 GiB memory and 100 GiB SSD at 0 GiB-month to 2 vCPU, 8 GiB memory and 12,525 GiB SSD at 10,000 GiB-month. From 100,000 GiB-month the workload exceeds the planning range and the target is unpriced. Curve assumptions

• Request meters remain at their independently authored defaults. Other native meters and workload assumptions retain their explicitly displayed default quantities. Workload translation and capacity assumptions are not benchmark measurements.
• Native monthly usage priced at the cited provider list prices; listed target allowances apply where present, excluding invoice credits, taxes and negotiated discounts. Rates as of 2026-10-22: eastus → us-central1, USD/month.
• Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
• Samples of explicit prices are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
• Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve’s workload note.
• Rates are cited provider list prices, editable for discounts, commitments or another region. Workload translation and capacity coefficients remain editable planning assumptions, not benchmark measurements or a commercial quote.
• Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
• Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
• Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
• A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
• This exact directed mapping has a design profile. Cost modeling does not establish an implemented or deployable adapter.
• Authored planning assumptions, not measured adapter capacity. Origin rates are cited first-tier list prices, before free allowances and discounts.
• A cost scenario does not establish backend availability, protocol fidelity or production readiness. Registry serving status remains independent.
• Provisioned compute and RAM are priced by resource-hour; operations are independently authored. Database size cannot be inferred from dollars alone.
• Aurora/AlloyDB, MySQL/PostgreSQL and proxied targets retain their distinct backend contracts. HA, replicas and proxy allocations must be selected explicitly.
• Flexible Server memory is included in the vCore price; the memory meter is zero so RAM is not counted twice.
• Cloud SQL Enterprise edition (MySQL) publishes separate vCPU, memory and SSD prices for zonal instances; a high-availability (regional) instance bills exactly twice each, which the standby copy reproduces. Enterprise Plus, committed-use discounts, backups (USD 0.08 per GiB-month) and idle IPv4 addresses (0.01 per hour) are not selected.
• Row-store throughput (capacityOpsPerVcpuSecond, default 1500) is measured-by-tensor9 as a lower bound: the DynamoDB adapter on Cloud SQL db-custom-2-7680 (2 vCPU, PostgreSQL 16, us-west1) served 2,974 ops/s of YCSB-A at 16 threads without recorded saturation (src/main/kotlin/t9/prime/equiv/generated/eval/CloudsqlPostgresqlYcsbAT16GoYcsbV1_0_0.kt). Published CPU-bound pgbench reaches 3,101 read-write transactions and 20,289 point reads per vCPU-second (AWS z1d.2xlarge, PostgreSQL 14.5), so actual capacity is likely higher. Reads and writes share one coefficient: at the same adapter version, read-only YCSB-C was not faster than 50%-update YCSB-A.
• Log-broker throughput (capacityStreamMiBPerVcpuSecond 20 at 0.5 utilization, 4 GiB RAM per vCPU) is provider-documented by Google Managed Service for Apache Kafka sizing (https://docs.cloud.google.com/managed-service-for-apache-kafka/docs/plan-cluster-size): write-equivalent bytes are replicated writes plus a quarter of reads. Producer batches below 10 KB lower per-CPU throughput; that penalty is not modeled.
• Disk utilization 0.8 is provider-documented headroom below Cloud SQL automatic storage increase, which triggers near 91-95% full (https://docs.cloud.google.com/sql/docs/postgres/instance-settings). The 20 GiB reserve exceeds PostgreSQL’s 1 GB default max_wal_size; the remainder of that reserve is unmeasured.
• CPU tiers double from 2 vCPUs to the target’s largest node at 4 GiB per vCPU; each target’s documented largest node bounds CPU, RAM, RAM per vCPU and disk, and the durable staging database uses Cloud SQL Enterprise (96 vCPU, 6.5 GiB per vCPU, 624 GiB, 64 TiB). Targets billed per capacity unit or throughput unit are sized by their backend instead.
• No public evidence: peak/mean work (2) and the RAM working-set fraction (0.1). Proposed measurements: the p99 one-minute rate over the monthly mean from customer CloudWatch metrics; the buffer hit ratio while stepping RAM under a fixed YCSB-B load.
• Node bounds: Cloud SQL Enterprise allows 1-96 vCPUs at 0.9-6.5 GB per vCPU and up to 64 TB with a dedicated vCPU (https://docs.cloud.google.com/sql/docs/postgres/instance-settings).
• Stored GiB already includes the origin family’s physical footprint assumptions; no second storage amplification is applied.
• The workload family already selected resource-hours; the throughput coefficient is not applied again.
• Copies and allocation fractions change cost only; they do not increase modeled primary capacity.
• Azure Retail Prices API: https://prices.azure.com/api/retail/prices
• Cloud SQL pricing: https://cloud.google.com/sql/pricing

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied. Excluded costs and workload features:

• Additional network transfer, backups, KMS, one-time migration and operational labor unless an explicit meter includes them.
• Destination application execution and separately billed downstream services; supply those allocations separately.
• Aurora per-IO, serverless-capacity, backup and proxy charges; reserved/committed-use purchase options.
• Taxes, discounts, credits and free-tier allowances not explicitly listed by this model.
• Unmodeled dependent services, task execution and operations outside the selected workload family.

List prices read: 2026-10-22. Model: plan-e57f7ffe0ebc14b9a56d6bfe1599e4ef0c1ee6f2 / 2026-10-22.planning.2. Curve: workload-2. Sources: Azure Retail Prices API, Cloud SQL pricing.

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Azure MySQL Flexible Server · Database writes

Feature: Azure MySQL Flexible Server. Estimated monthly service charges by Database writes. Adapter hosting and Tensor9 fees are excluded. Source: eastus; target: us-central1; currency: USD. Comparison pills describe all sampled scale points; amounts beside each service are for the named workload. Costs The Same means within 20% at every point. Costs Depend includes mixed results and unpriced samples. Sampled monthly charges in USD, rounded to cents. Difference means target minus origin; a positive difference means the target costs more. Estimated allocation, not benchmark calibrated: sized at 2 vCPU, 8 GiB memory and 100 GiB SSD at every sample. Curve assumptions

• Source compute and stored data remain independent; a throughput view needs explicit workload inputs. Other native meters and workload assumptions retain their explicitly displayed default quantities. Workload translation and capacity assumptions are not benchmark measurements.
• Native monthly usage priced at the cited provider list prices; listed target allowances apply where present, excluding invoice credits, taxes and negotiated discounts. Rates as of 2026-10-22: eastus → us-central1, USD/month.
• Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
• Samples of explicit prices are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
• Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve’s workload note.
• Rates are cited provider list prices, editable for discounts, commitments or another region. Workload translation and capacity coefficients remain editable planning assumptions, not benchmark measurements or a commercial quote.
• Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
• Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
• Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
• A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
• This exact directed mapping has a design profile. Cost modeling does not establish an implemented or deployable adapter.
• Authored planning assumptions, not measured adapter capacity. Origin rates are cited first-tier list prices, before free allowances and discounts.
• A cost scenario does not establish backend availability, protocol fidelity or production readiness. Registry serving status remains independent.
• Provisioned compute and RAM are priced by resource-hour; operations are independently authored. Database size cannot be inferred from dollars alone.
• Aurora/AlloyDB, MySQL/PostgreSQL and proxied targets retain their distinct backend contracts. HA, replicas and proxy allocations must be selected explicitly.
• Flexible Server memory is included in the vCore price; the memory meter is zero so RAM is not counted twice.
• Cloud SQL Enterprise edition (MySQL) publishes separate vCPU, memory and SSD prices for zonal instances; a high-availability (regional) instance bills exactly twice each, which the standby copy reproduces. Enterprise Plus, committed-use discounts, backups (USD 0.08 per GiB-month) and idle IPv4 addresses (0.01 per hour) are not selected.
• Row-store throughput (capacityOpsPerVcpuSecond, default 1500) is measured-by-tensor9 as a lower bound: the DynamoDB adapter on Cloud SQL db-custom-2-7680 (2 vCPU, PostgreSQL 16, us-west1) served 2,974 ops/s of YCSB-A at 16 threads without recorded saturation (src/main/kotlin/t9/prime/equiv/generated/eval/CloudsqlPostgresqlYcsbAT16GoYcsbV1_0_0.kt). Published CPU-bound pgbench reaches 3,101 read-write transactions and 20,289 point reads per vCPU-second (AWS z1d.2xlarge, PostgreSQL 14.5), so actual capacity is likely higher. Reads and writes share one coefficient: at the same adapter version, read-only YCSB-C was not faster than 50%-update YCSB-A.
• Log-broker throughput (capacityStreamMiBPerVcpuSecond 20 at 0.5 utilization, 4 GiB RAM per vCPU) is provider-documented by Google Managed Service for Apache Kafka sizing (https://docs.cloud.google.com/managed-service-for-apache-kafka/docs/plan-cluster-size): write-equivalent bytes are replicated writes plus a quarter of reads. Producer batches below 10 KB lower per-CPU throughput; that penalty is not modeled.
• Disk utilization 0.8 is provider-documented headroom below Cloud SQL automatic storage increase, which triggers near 91-95% full (https://docs.cloud.google.com/sql/docs/postgres/instance-settings). The 20 GiB reserve exceeds PostgreSQL’s 1 GB default max_wal_size; the remainder of that reserve is unmeasured.
• CPU tiers double from 2 vCPUs to the target’s largest node at 4 GiB per vCPU; each target’s documented largest node bounds CPU, RAM, RAM per vCPU and disk, and the durable staging database uses Cloud SQL Enterprise (96 vCPU, 6.5 GiB per vCPU, 624 GiB, 64 TiB). Targets billed per capacity unit or throughput unit are sized by their backend instead.
• No public evidence: peak/mean work (2) and the RAM working-set fraction (0.1). Proposed measurements: the p99 one-minute rate over the monthly mean from customer CloudWatch metrics; the buffer hit ratio while stepping RAM under a fixed YCSB-B load.
• Node bounds: Cloud SQL Enterprise allows 1-96 vCPUs at 0.9-6.5 GB per vCPU and up to 64 TB with a dedicated vCPU (https://docs.cloud.google.com/sql/docs/postgres/instance-settings).
• Stored GiB already includes the origin family’s physical footprint assumptions; no second storage amplification is applied.
• The workload family already selected resource-hours; the throughput coefficient is not applied again.
• Copies and allocation fractions change cost only; they do not increase modeled primary capacity.
• Azure Retail Prices API: https://prices.azure.com/api/retail/prices
• Cloud SQL pricing: https://cloud.google.com/sql/pricing

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied. Excluded costs and workload features:

• Additional network transfer, backups, KMS, one-time migration and operational labor unless an explicit meter includes them.
• Destination application execution and separately billed downstream services; supply those allocations separately.
• Aurora per-IO, serverless-capacity, backup and proxy charges; reserved/committed-use purchase options.
• Taxes, discounts, credits and free-tier allowances not explicitly listed by this model.
• Unmodeled dependent services, task execution and operations outside the selected workload family.

List prices read: 2026-10-22. Model: plan-e57f7ffe0ebc14b9a56d6bfe1599e4ef0c1ee6f2 / 2026-10-22.planning.2. Curve: workload-3. Sources: Azure Retail Prices API, Cloud SQL pricing.

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Azure MySQL Flexible Server → RDS MySQL

Origin API: azure::1.0.0::mysql::flexible. Target backend: aws::1.0.0::rds::mysql. Designed mapping. This cost model describes an intended adapter. Its estimated price does not establish a delivered or selectable backend.

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Azure MySQL Flexible Server · Primary allocated compute

Feature: Azure MySQL Flexible Server. Estimated monthly service charges by Primary allocated compute. Adapter hosting and Tensor9 fees are excluded. Source: eastus; target: us-east-1; currency: USD. Comparison pills describe all sampled scale points; amounts beside each service are for the named workload. Costs The Same means within 20% at every point. Costs Depend includes mixed results and unpriced samples. Sampled monthly charges in USD, rounded to cents. Difference means target minus origin; a positive difference means the target costs more. Estimated allocation, not benchmark calibrated: sized from 2 vCPU, 8 GiB memory and 100 GiB SSD at 0 vCPU-hours/month to 64 vCPU, 256 GiB memory and 100 GiB SSD at 46,720 vCPU-hours/month. Curve assumptions

• CPU allocation does not imply an achieved transaction rate. Other native meters and workload assumptions retain their explicitly displayed default quantities. Workload translation and capacity assumptions are not benchmark measurements.
• Native monthly usage priced at the cited provider list prices; listed target allowances apply where present, excluding invoice credits, taxes and negotiated discounts. Rates as of 2026-10-22: eastus → us-east-1, USD/month.
• Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
• Samples of explicit prices are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
• Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve’s workload note.
• Rates are cited provider list prices, editable for discounts, commitments or another region. Workload translation and capacity coefficients remain editable planning assumptions, not benchmark measurements or a commercial quote.
• Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
• Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
• Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
• A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
• This exact directed mapping has a design profile. Cost modeling does not establish an implemented or deployable adapter.
• Authored planning assumptions, not measured adapter capacity. Origin rates are cited first-tier list prices, before free allowances and discounts.
• A cost scenario does not establish backend availability, protocol fidelity or production readiness. Registry serving status remains independent.
• Provisioned compute and RAM are priced by resource-hour; operations are independently authored. Database size cannot be inferred from dollars alone.
• Aurora/AlloyDB, MySQL/PostgreSQL and proxied targets retain their distinct backend contracts. HA, replicas and proxy allocations must be selected explicitly.
• Flexible Server memory is included in the vCore price; the memory meter is zero so RAM is not counted twice.
• RDS for MySQL on db.m6i, the class the RDS reference model uses: vCPU and memory rates decompose two same-vCPU instances that differ only in memory. Multi-AZ with one standby bills exactly twice the instance and gp3 storage, which the standby copy reproduces. gp3 includes 3,000 IOPS and 125 MiB/s below 400 GiB; provisioned IOPS (USD 0.02 per IOPS-month), throughput (0.08 per MiBps-month), Graviton classes (db.m7g/r7g decompose to 0.0485 per vCPU-hour and 0.008875 per GiB-hour) and reserved instances are not selected.
• Row-store throughput (capacityOpsPerVcpuSecond, default 1500) is measured-by-tensor9 as a lower bound: the DynamoDB adapter on Cloud SQL db-custom-2-7680 (2 vCPU, PostgreSQL 16, us-west1) served 2,974 ops/s of YCSB-A at 16 threads without recorded saturation (src/main/kotlin/t9/prime/equiv/generated/eval/CloudsqlPostgresqlYcsbAT16GoYcsbV1_0_0.kt). Published CPU-bound pgbench reaches 3,101 read-write transactions and 20,289 point reads per vCPU-second (AWS z1d.2xlarge, PostgreSQL 14.5), so actual capacity is likely higher. Reads and writes share one coefficient: at the same adapter version, read-only YCSB-C was not faster than 50%-update YCSB-A.
• Log-broker throughput (capacityStreamMiBPerVcpuSecond 20 at 0.5 utilization, 4 GiB RAM per vCPU) is provider-documented by Google Managed Service for Apache Kafka sizing (https://docs.cloud.google.com/managed-service-for-apache-kafka/docs/plan-cluster-size): write-equivalent bytes are replicated writes plus a quarter of reads. Producer batches below 10 KB lower per-CPU throughput; that penalty is not modeled.
• Disk utilization 0.8 is provider-documented headroom below Cloud SQL automatic storage increase, which triggers near 91-95% full (https://docs.cloud.google.com/sql/docs/postgres/instance-settings). The 20 GiB reserve exceeds PostgreSQL’s 1 GB default max_wal_size; the remainder of that reserve is unmeasured.
• CPU tiers double from 2 vCPUs to the target’s largest node at 4 GiB per vCPU; each target’s documented largest node bounds CPU, RAM, RAM per vCPU and disk, and the durable staging database uses Cloud SQL Enterprise (96 vCPU, 6.5 GiB per vCPU, 624 GiB, 64 TiB). Targets billed per capacity unit or throughput unit are sized by their backend instead.
• No public evidence: peak/mean work (2) and the RAM working-set fraction (0.1). Proposed measurements: the p99 one-minute rate over the monthly mean from customer CloudWatch metrics; the buffer hit ratio while stepping RAM under a fixed YCSB-B load.
• Node bounds: RDS db.r6i.32xlarge has 128 vCPUs and 1,024 GiB (https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Concepts.DBInstanceClass.Summary.html); gp3 storage holds 20-65,536 GiB (https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/CHAP_Storage.html).
• Stored GiB already includes the origin family’s physical footprint assumptions; no second storage amplification is applied.
• The workload family already selected resource-hours; the throughput coefficient is not applied again.
• Copies and allocation fractions change cost only; they do not increase modeled primary capacity.
• Azure Retail Prices API: https://prices.azure.com/api/retail/prices
• AWS Price List API: https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonRDS/current/us-east-1/index.json
• AWS Price List API, AWSDataTransfer: https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AWSDataTransfer/current/us-east-1/index.json

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied. Excluded costs and workload features:

• Additional network transfer, backups, KMS, one-time migration and operational labor unless an explicit meter includes them.
• Destination application execution and separately billed downstream services; supply those allocations separately.
• Aurora per-IO, serverless-capacity, backup and proxy charges; reserved/committed-use purchase options.
• Taxes, discounts, credits and free-tier allowances not explicitly listed by this model.
• Unmodeled dependent services, task execution and operations outside the selected workload family.

List prices read: 2026-10-22. Model: plan-5ad440e5920796f270acdf637ebd19abecf853f5 / 2026-10-22.planning.2. Curve: workload-1. Sources: Azure Retail Prices API, AWS Price List API, AWS Price List API, AWSDataTransfer.

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Azure MySQL Flexible Server · Stored data

Feature: Azure MySQL Flexible Server. Estimated monthly service charges by Stored data. Adapter hosting and Tensor9 fees are excluded. Source: eastus; target: us-east-1; currency: USD. Comparison pills describe all sampled scale points; amounts beside each service are for the named workload. Costs The Same means within 20% at every point. Costs Depend includes mixed results and unpriced samples. Sampled monthly charges in USD, rounded to cents. Difference means target minus origin; a positive difference means the target costs more. Estimated allocation, not benchmark calibrated: sized from 2 vCPU, 8 GiB memory and 100 GiB SSD at 0 GiB-month to 2 vCPU, 8 GiB memory and 12,525 GiB SSD at 10,000 GiB-month. From 100,000 GiB-month the workload exceeds the planning range and the target is unpriced. Curve assumptions

• Request meters remain at their independently authored defaults. Other native meters and workload assumptions retain their explicitly displayed default quantities. Workload translation and capacity assumptions are not benchmark measurements.
• Native monthly usage priced at the cited provider list prices; listed target allowances apply where present, excluding invoice credits, taxes and negotiated discounts. Rates as of 2026-10-22: eastus → us-east-1, USD/month.
• Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
• Samples of explicit prices are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
• Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve’s workload note.
• Rates are cited provider list prices, editable for discounts, commitments or another region. Workload translation and capacity coefficients remain editable planning assumptions, not benchmark measurements or a commercial quote.
• Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
• Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
• Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
• A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
• This exact directed mapping has a design profile. Cost modeling does not establish an implemented or deployable adapter.
• Authored planning assumptions, not measured adapter capacity. Origin rates are cited first-tier list prices, before free allowances and discounts.
• A cost scenario does not establish backend availability, protocol fidelity or production readiness. Registry serving status remains independent.
• Provisioned compute and RAM are priced by resource-hour; operations are independently authored. Database size cannot be inferred from dollars alone.
• Aurora/AlloyDB, MySQL/PostgreSQL and proxied targets retain their distinct backend contracts. HA, replicas and proxy allocations must be selected explicitly.
• Flexible Server memory is included in the vCore price; the memory meter is zero so RAM is not counted twice.
• RDS for MySQL on db.m6i, the class the RDS reference model uses: vCPU and memory rates decompose two same-vCPU instances that differ only in memory. Multi-AZ with one standby bills exactly twice the instance and gp3 storage, which the standby copy reproduces. gp3 includes 3,000 IOPS and 125 MiB/s below 400 GiB; provisioned IOPS (USD 0.02 per IOPS-month), throughput (0.08 per MiBps-month), Graviton classes (db.m7g/r7g decompose to 0.0485 per vCPU-hour and 0.008875 per GiB-hour) and reserved instances are not selected.
• Row-store throughput (capacityOpsPerVcpuSecond, default 1500) is measured-by-tensor9 as a lower bound: the DynamoDB adapter on Cloud SQL db-custom-2-7680 (2 vCPU, PostgreSQL 16, us-west1) served 2,974 ops/s of YCSB-A at 16 threads without recorded saturation (src/main/kotlin/t9/prime/equiv/generated/eval/CloudsqlPostgresqlYcsbAT16GoYcsbV1_0_0.kt). Published CPU-bound pgbench reaches 3,101 read-write transactions and 20,289 point reads per vCPU-second (AWS z1d.2xlarge, PostgreSQL 14.5), so actual capacity is likely higher. Reads and writes share one coefficient: at the same adapter version, read-only YCSB-C was not faster than 50%-update YCSB-A.
• Log-broker throughput (capacityStreamMiBPerVcpuSecond 20 at 0.5 utilization, 4 GiB RAM per vCPU) is provider-documented by Google Managed Service for Apache Kafka sizing (https://docs.cloud.google.com/managed-service-for-apache-kafka/docs/plan-cluster-size): write-equivalent bytes are replicated writes plus a quarter of reads. Producer batches below 10 KB lower per-CPU throughput; that penalty is not modeled.
• Disk utilization 0.8 is provider-documented headroom below Cloud SQL automatic storage increase, which triggers near 91-95% full (https://docs.cloud.google.com/sql/docs/postgres/instance-settings). The 20 GiB reserve exceeds PostgreSQL’s 1 GB default max_wal_size; the remainder of that reserve is unmeasured.
• CPU tiers double from 2 vCPUs to the target’s largest node at 4 GiB per vCPU; each target’s documented largest node bounds CPU, RAM, RAM per vCPU and disk, and the durable staging database uses Cloud SQL Enterprise (96 vCPU, 6.5 GiB per vCPU, 624 GiB, 64 TiB). Targets billed per capacity unit or throughput unit are sized by their backend instead.
• No public evidence: peak/mean work (2) and the RAM working-set fraction (0.1). Proposed measurements: the p99 one-minute rate over the monthly mean from customer CloudWatch metrics; the buffer hit ratio while stepping RAM under a fixed YCSB-B load.
• Node bounds: RDS db.r6i.32xlarge has 128 vCPUs and 1,024 GiB (https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Concepts.DBInstanceClass.Summary.html); gp3 storage holds 20-65,536 GiB (https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/CHAP_Storage.html).
• Stored GiB already includes the origin family’s physical footprint assumptions; no second storage amplification is applied.
• The workload family already selected resource-hours; the throughput coefficient is not applied again.
• Copies and allocation fractions change cost only; they do not increase modeled primary capacity.
• Azure Retail Prices API: https://prices.azure.com/api/retail/prices
• AWS Price List API: https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonRDS/current/us-east-1/index.json
• AWS Price List API, AWSDataTransfer: https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AWSDataTransfer/current/us-east-1/index.json

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied. Excluded costs and workload features:

• Additional network transfer, backups, KMS, one-time migration and operational labor unless an explicit meter includes them.
• Destination application execution and separately billed downstream services; supply those allocations separately.
• Aurora per-IO, serverless-capacity, backup and proxy charges; reserved/committed-use purchase options.
• Taxes, discounts, credits and free-tier allowances not explicitly listed by this model.
• Unmodeled dependent services, task execution and operations outside the selected workload family.

List prices read: 2026-10-22. Model: plan-5ad440e5920796f270acdf637ebd19abecf853f5 / 2026-10-22.planning.2. Curve: workload-2. Sources: Azure Retail Prices API, AWS Price List API, AWS Price List API, AWSDataTransfer.

​

Azure MySQL Flexible Server · Database writes

Feature: Azure MySQL Flexible Server. Estimated monthly service charges by Database writes. Adapter hosting and Tensor9 fees are excluded. Source: eastus; target: us-east-1; currency: USD. Comparison pills describe all sampled scale points; amounts beside each service are for the named workload. Costs The Same means within 20% at every point. Costs Depend includes mixed results and unpriced samples. Sampled monthly charges in USD, rounded to cents. Difference means target minus origin; a positive difference means the target costs more. Estimated allocation, not benchmark calibrated: sized at 2 vCPU, 8 GiB memory and 100 GiB SSD at every sample. Curve assumptions

• Source compute and stored data remain independent; a throughput view needs explicit workload inputs. Other native meters and workload assumptions retain their explicitly displayed default quantities. Workload translation and capacity assumptions are not benchmark measurements.
• Native monthly usage priced at the cited provider list prices; listed target allowances apply where present, excluding invoice credits, taxes and negotiated discounts. Rates as of 2026-10-22: eastus → us-east-1, USD/month.
• Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
• Samples of explicit prices are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
• Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve’s workload note.
• Rates are cited provider list prices, editable for discounts, commitments or another region. Workload translation and capacity coefficients remain editable planning assumptions, not benchmark measurements or a commercial quote.
• Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
• Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
• Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
• A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
• This exact directed mapping has a design profile. Cost modeling does not establish an implemented or deployable adapter.
• Authored planning assumptions, not measured adapter capacity. Origin rates are cited first-tier list prices, before free allowances and discounts.
• A cost scenario does not establish backend availability, protocol fidelity or production readiness. Registry serving status remains independent.
• Provisioned compute and RAM are priced by resource-hour; operations are independently authored. Database size cannot be inferred from dollars alone.
• Aurora/AlloyDB, MySQL/PostgreSQL and proxied targets retain their distinct backend contracts. HA, replicas and proxy allocations must be selected explicitly.
• Flexible Server memory is included in the vCore price; the memory meter is zero so RAM is not counted twice.
• RDS for MySQL on db.m6i, the class the RDS reference model uses: vCPU and memory rates decompose two same-vCPU instances that differ only in memory. Multi-AZ with one standby bills exactly twice the instance and gp3 storage, which the standby copy reproduces. gp3 includes 3,000 IOPS and 125 MiB/s below 400 GiB; provisioned IOPS (USD 0.02 per IOPS-month), throughput (0.08 per MiBps-month), Graviton classes (db.m7g/r7g decompose to 0.0485 per vCPU-hour and 0.008875 per GiB-hour) and reserved instances are not selected.
• Row-store throughput (capacityOpsPerVcpuSecond, default 1500) is measured-by-tensor9 as a lower bound: the DynamoDB adapter on Cloud SQL db-custom-2-7680 (2 vCPU, PostgreSQL 16, us-west1) served 2,974 ops/s of YCSB-A at 16 threads without recorded saturation (src/main/kotlin/t9/prime/equiv/generated/eval/CloudsqlPostgresqlYcsbAT16GoYcsbV1_0_0.kt). Published CPU-bound pgbench reaches 3,101 read-write transactions and 20,289 point reads per vCPU-second (AWS z1d.2xlarge, PostgreSQL 14.5), so actual capacity is likely higher. Reads and writes share one coefficient: at the same adapter version, read-only YCSB-C was not faster than 50%-update YCSB-A.
• Log-broker throughput (capacityStreamMiBPerVcpuSecond 20 at 0.5 utilization, 4 GiB RAM per vCPU) is provider-documented by Google Managed Service for Apache Kafka sizing (https://docs.cloud.google.com/managed-service-for-apache-kafka/docs/plan-cluster-size): write-equivalent bytes are replicated writes plus a quarter of reads. Producer batches below 10 KB lower per-CPU throughput; that penalty is not modeled.
• Disk utilization 0.8 is provider-documented headroom below Cloud SQL automatic storage increase, which triggers near 91-95% full (https://docs.cloud.google.com/sql/docs/postgres/instance-settings). The 20 GiB reserve exceeds PostgreSQL’s 1 GB default max_wal_size; the remainder of that reserve is unmeasured.
• CPU tiers double from 2 vCPUs to the target’s largest node at 4 GiB per vCPU; each target’s documented largest node bounds CPU, RAM, RAM per vCPU and disk, and the durable staging database uses Cloud SQL Enterprise (96 vCPU, 6.5 GiB per vCPU, 624 GiB, 64 TiB). Targets billed per capacity unit or throughput unit are sized by their backend instead.
• No public evidence: peak/mean work (2) and the RAM working-set fraction (0.1). Proposed measurements: the p99 one-minute rate over the monthly mean from customer CloudWatch metrics; the buffer hit ratio while stepping RAM under a fixed YCSB-B load.
• Node bounds: RDS db.r6i.32xlarge has 128 vCPUs and 1,024 GiB (https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Concepts.DBInstanceClass.Summary.html); gp3 storage holds 20-65,536 GiB (https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/CHAP_Storage.html).
• Stored GiB already includes the origin family’s physical footprint assumptions; no second storage amplification is applied.
• The workload family already selected resource-hours; the throughput coefficient is not applied again.
• Copies and allocation fractions change cost only; they do not increase modeled primary capacity.
• Azure Retail Prices API: https://prices.azure.com/api/retail/prices
• AWS Price List API: https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonRDS/current/us-east-1/index.json
• AWS Price List API, AWSDataTransfer: https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AWSDataTransfer/current/us-east-1/index.json

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied. Excluded costs and workload features:

• Additional network transfer, backups, KMS, one-time migration and operational labor unless an explicit meter includes them.
• Destination application execution and separately billed downstream services; supply those allocations separately.
• Aurora per-IO, serverless-capacity, backup and proxy charges; reserved/committed-use purchase options.
• Taxes, discounts, credits and free-tier allowances not explicitly listed by this model.
• Unmodeled dependent services, task execution and operations outside the selected workload family.

List prices read: 2026-10-22. Model: plan-5ad440e5920796f270acdf637ebd19abecf853f5 / 2026-10-22.planning.2. Curve: workload-3. Sources: Azure Retail Prices API, AWS Price List API, AWS Price List API, AWSDataTransfer. See the service catalog for operation coverage, supported directions and backend limitations.