Compare Scenarios
Side-by-side comparison with decision path analysis. Every dimension traces back to topology, risk propagation, simulation, and advisor intelligence.
Select Scenarios to Compare
Left Scenario
AI / RAG
Multi-Tenant SaaS
Analytics
Financial Ledger
Read-Heavy
Multi-Tenant SaaS
Write-Heavy
Marketplace
Event-Driven
Financial Ledger
Realtime Collab
Realtime Collab
Financial Ledger
Write-Heavy
AI / RAG
Multi-Tenant SaaS
Event-Driven
Analytics
Read-Heavy
Realtime Collab
Search-Heavy
Event-Driven
Event-Driven
Marketplace
Write-Heavy
Right Scenario
AI / RAG
Multi-Tenant SaaS
Analytics
Financial Ledger
Read-Heavy
Multi-Tenant SaaS
Write-Heavy
Marketplace
Event-Driven
Financial Ledger
Realtime Collab
Realtime Collab
Financial Ledger
Write-Heavy
AI / RAG
Multi-Tenant SaaS
Event-Driven
Analytics
Read-Heavy
Realtime Collab
Search-Heavy
Event-Driven
Event-Driven
Marketplace
Write-Heavy
Topology at a Glance
Architecture Comparison
Write-Heavy Transactional Platform is both simpler and lower-risk than Two-Sided Marketplace Platform
Write-Heavy Transactional Platform is the simpler architecture. Write-Heavy Transactional Platform carries lower operational risk. They share 4 component(s). Two-Sided Marketplace Platform has 4 unique risk(s); Write-Heavy Transactional Platform has 3.
19
Nodes
0
Edges
5
Risks
2
Seeds
0
Strengths
5
Adv. Risks
11
Nodes
5
Edges
4
Risks
3
Seeds
2
Strengths
4
Adv. Risks
Comparison Dimensions
Complexity
Two-Sided Marketplace Platform
expert complexity, 19 nodes, 0 edges, 5 risks, 2 simulation seeds
Write-Heavy Transactional Platform
high complexity, 11 nodes, 5 edges, 4 risks, 3 simulation seeds
Write-Heavy Transactional Platform is simpler: high operational complexity with 11 topology nodes vs 19 for Two-Sided Marketplace Platform.
Operational Risk
Two-Sided Marketplace Platform
5 risks (top: high), 5 high/critical, 1 confirmed by simulation
Write-Heavy Transactional Platform
4 risks (top: high), 3 high/critical, 0 confirmed by simulation
Write-Heavy Transactional Platform has lower operational risk: weighted severity score 14 vs 20 (0 vs 1 simulation-confirmed).
Scalability
Two-Sided Marketplace Platform
4 scaling thresholds, 3 migration paths, 6 advisor scaling signals
Write-Heavy Transactional Platform
4 scaling thresholds, 3 migration paths, 4 advisor scaling signals
Two-Sided Marketplace Platform has more defined scaling paths: 4 thresholds and 3 migration paths.
Operational Maturity
Two-Sided Marketplace Platform
Advisor assessment: Advanced; recommended team: Platform Engineering Team; 15 operational requirements
Write-Heavy Transactional Platform
Advisor assessment: Advanced; recommended team: Experienced Backend Team; 7 operational requirements
Both scenarios require equivalent team maturity: Advanced.
Observability
Two-Sided Marketplace Platform
5 watched metrics, 7 observability recommendations, 2 simulation seeds
Write-Heavy Transactional Platform
6 watched metrics, 4 observability recommendations, 3 simulation seeds
Write-Heavy Transactional Platform has lower observability burden: 6 watched metrics vs 5.
Generator Readiness
Two-Sided Marketplace Platform
generator relevance documented; topology generation relevance noted; simulation relevance noted; 2 seeds with generator notes
Write-Heavy Transactional Platform
generator relevance documented; topology generation relevance noted; simulation relevance noted; 3 seeds with generator notes
Both scenarios have comparable generator readiness at this stage. Generator support is preliminary. Neither scenario should be treated as fully generation-ready.
Architecture Components
Shared (4)
Only in Two-Sided Marketplace Platform (15)
Only in Write-Heavy Transactional Platform (7)
Operational Risks
Shared (1)
Only in Two-Sided Marketplace Platform (4)
Only in Write-Heavy Transactional Platform (3)
Consistency Guarantees
Only Write-Heavy Transactional Platform (1)
Moving from Write-Heavy Transactional Platform to Two-Sided Marketplace Platform
Green = kept, red = lost (the target explicitly excludes it), amber = unproven (the target has made no claim, not the same as losing it).
Only 'Write-Heavy Transactional Platform' claims: atomic_multi_object.
Tradeoff Summary
Complexity vs Risk
Two-Sided Marketplace Platform has expert complexity. Write-Heavy Transactional Platform has high complexity. Simpler systems often carry different (not necessarily fewer) risks.
Two-Sided Marketplace Platform
Two-Sided Marketplace Platform: 5 risks (top: high), 5 high/critical, 1 confirmed by simulation
Write-Heavy Transactional Platform
Write-Heavy Transactional Platform: 4 risks (top: high), 3 high/critical, 0 confirmed by simulation
Scaling Path
Two-Sided Marketplace Platform offers 4 defined scaling thresholds. Write-Heavy Transactional Platform offers 4. More defined paths means clearer evolution steps but also more anticipated growth.
Two-Sided Marketplace Platform
4 scaling thresholds, 3 migration paths, 6 advisor scaling signals
Write-Heavy Transactional Platform
4 scaling thresholds, 3 migration paths, 4 advisor scaling signals
Team Maturity Requirement
Write-Heavy Transactional Platform can be operated by a less experienced team. Two-Sided Marketplace Platform requires deeper operational expertise.
Two-Sided Marketplace Platform
Advisor assessment: Advanced; recommended team: Platform Engineering Team; 15 operational requirements
Write-Heavy Transactional Platform
Advisor assessment: Advanced; recommended team: Experienced Backend Team; 7 operational requirements
Architecture Strengths vs Risks Balance
The advisor identifies strengths and risks grounded in knowledge relationships. A higher strengths-to-risks ratio suggests better mitigation coverage in the current topology.
Two-Sided Marketplace Platform
0 strengths, 5 risks
Write-Heavy Transactional Platform
2 strengths, 4 risks
Migration Considerations
Migration Step 1
Two-Sided Marketplace Platform
Monolithic marketplace application with single database → Event-driven marketplace with Kafka + saga-based checkout flow
Write-Heavy Transactional Platform
Single PostgreSQL with synchronous dual-write (DB + Kafka in application code) → PostgreSQL + outbox pattern + WAL CDC relay to Kafka
Both scenarios define a migration step at this stage. Two-Sided Marketplace Platform: triggered by 'Checkout failures from payment provider unavailability causi'. Write-Heavy Transactional Platform: triggered by 'Dual-write inconsistency events observed in production: DB w'.
Migration Step 2
Two-Sided Marketplace Platform
PostgreSQL full-text search for listing discovery → Elasticsearch for listing search with CDC-based indexing
Write-Heavy Transactional Platform
PostgreSQL + PgBouncer + outbox + Kafka CDC → Domain-partitioned PostgreSQL + separate write services per partition
Both scenarios define a migration step at this stage. Two-Sided Marketplace Platform: triggered by 'Listing search p99 > 1s; faceted navigation (category + pric'. Write-Heavy Transactional Platform: triggered by 'Primary write CPU > 70% sustained during peak windows; WAL v'.
Migration Step 3
Two-Sided Marketplace Platform
Monolithic PostgreSQL serving all domain writes → Domain-separated databases with event-based cross-domain data propagation
Write-Heavy Transactional Platform
PostgreSQL + Kafka CDC → Event sourcing: append-only event log with read model projections
Both scenarios define a migration step at this stage. Two-Sided Marketplace Platform: triggered by 'Domain teams stepping on each other's schema migrations; dat'. Write-Heavy Transactional Platform: triggered by 'Audit completeness requirements grow beyond point-in-time ba'.
Advisor Notes
Strength: Write-heavy transactional workloads that emit downstream events (order placed, payment captured) benefit from the outbox pattern…
Write-heavy transactional workloads that emit downstream events (order placed, payment captured) benefit from the outbox pattern to ensure events are published exactly when the database transaction commits: never before, never after. Key trade-off: Adds one INSERT per transaction to the outbox table: minor but nonzero write amplification. Operational note: Outbox table grows with write volume: implement TTL-based cleanup or partition pruning. Evidence: Payment processors like Stripe use outbox-style patterns to ensure webhook delivery matches transaction commits.
Risk (high): Hot Partition
One partition (a database shard, a Kafka topic partition, a Redis hash slot) receives traffic so far above its peers that it saturates while the others sit idle. Aggregate capacity looks healthy, but the hot partition throttles or lags, and everything routed to it degrades. The cause is skew in how keys map to partitions, and the fix depends on whether the skew is spread across many keys or concentrated in one.
Risk (high): Write Amplification Cascade
Each logical application write triggers multiple physical writes through index maintenance, WAL generation, MVCC versioning, and replication, causing actual disk IOPS to exceed the provisioned I/O ceiling while the logical write rate appears modest.
Shared Operational Requirements
Both scenarios require: Apache Kafka: scenario has team_maturity below senior, Apache Kafka: scenario uses Kafka for event streaming or CDC, Event stream operations expertise.
Supporting Evidence · 16 items
Coverage Warnings
- ⚠Two-Sided Marketplace Platform: fewer than 2 architectural strengths identified. the risk/complexity dimensions are present but the strength analysis is thin. Consider enriching the relationship YAMLs referenced by this scenario to improve coverage.
Limitations
- ·Comparison grounded in YAML knowledge only. Not measured from any production system.
- ·Winner assessments are deterministic heuristics, not absolute recommendations. Context, team preferences, and workload specifics may change the conclusion.
- ·5 seed type(s) across both scenarios do not have execution previews. Risk confirmation for those types is unavailable.
Write-Heavy Transactional Platform is the recommended starting point over Two-Sided Marketplace Platform
Write-Heavy Transactional Platform leads on 3 weighted dimension(s): Complexity, Operational Risk, Observability. Weighted score: 5.5 vs 2.0 for Two-Sided Marketplace Platform.
Decision Intelligence
Architecture Decision Path
Structured reasoning for choosing between Two-Sided Marketplace Platform and Write-Heavy Transactional Platform. Every condition and trigger traces back to comparison dimensions, advisor insights, and topology evidence.
Write-Heavy Transactional Platform is the recommended starting point over Two-Sided Marketplace Platform
Write-Heavy Transactional Platform leads on 3 weighted dimension(s): Complexity, Operational Risk, Observability. Weighted score: 5.5 vs 2.0 for Two-Sided Marketplace Platform. The architectures share 4 component(s), reducing migration cost if you switch later. Write-Heavy Transactional Platform is the operationally simpler choice.
Where to Start
Start with Write-Heavy Transactional Platform
RightWrite-Heavy Transactional Platform has lower operational complexity. Starting here reduces risk and cognitive load. Migrate to the more capable architecture only when you hit concrete scaling or feature limits.
Complexity: high complexity, 11 nodes, 5 edges, 4 risks, 3 simulation seeds
Migrate when:
- PgBouncer wait_queue > 0 sustained; application p99 write latency rising faster than PostgreSQL p99; pool_mode=transaction showing >80% utilization → Increase PgBouncer pool_size incrementally; profile transaction duration to right-size pool; consider separate pools for write-heavy and read-only workloads
- PostgreSQL checkpoint_completion_target warnings in logs; wal_buffers flushing more than once per second; pg_stat_bgwriter shows checkpoints_req rising; write p99 > 20ms without query explanation → Tune checkpoint_completion_target to 0.9; increase wal_buffers to 64MB; move PostgreSQL WAL to a dedicated NVMe volume separate from data directory
- pg_locks shows contended rows with wait events > 5ms; write throughput plateauing despite available CPU; deadlock errors appearing in application logs → Partition the hot table by entity range or hash; introduce optimistic locking with retry for high-contention entities; consider queue-per-entity serialization via application-level lock tokens
Decision Flow
Does your team have the operational maturity to run Two-Sided Marketplace Platform (advanced rating)?
If Yes
Your team can operate Two-Sided Marketplace Platform. Continue to Step 2 to refine based on risk tolerance and workload fit.
If No
Prefer the lower-maturity option: right scenario.
Is operational stability and minimising production risk your primary concern over feature richness or scalability ceiling?
If Yes
Prefer Write-Heavy Transactional Platform: it carries lower operational risk weight per the advisor's assessment.
If No
Proceed to Step 3 to evaluate based on scaling requirements.
Do you expect your load to reach: Redis cache miss spike visible in monitoring; PostgreSQL query rate spiking for listing reads despite stable write volume; p99 listing API latency > 500ms during traffic spike events ?
If Yes
Left scenario has more defined scaling evolution paths for this growth pattern.
If No
If you don't expect to hit these scaling signals soon, prefer the simpler architecture and re-evaluate when load patterns become clearer.
Is operational simplicity (fewer moving parts, easier debugging, lower ops burden) more important than maximum architectural capability?
If Yes
Write-Heavy Transactional Platform is the simpler choice: Write-Heavy Transactional Platform is simpler: high operational complexity with 11 topology nodes vs 19 for Two-Sided Marketplace Platform.
If No
If capability and scalability ceiling matter more than simplicity, evaluate the higher-complexity scenario against your specific load model.
When to Choose Each Scenario
Two-Sided Marketplace Platform
LeftWhen you need well-defined scaling thresholds and migration paths
HighTwo-Sided Marketplace Platform has more documented scaling evolution steps (4 thresholds, 3 migration paths).
When your system requires decoupled async event processing
HighTwo-Sided Marketplace Platform includes event stream infrastructure (e.g., Kafka/Kinesis), enabling async decoupling between producers and consumers.
Write-Heavy Transactional Platform
RightWhen operational simplicity is a top priority
HighWrite-Heavy Transactional Platform has lower operational complexity: fewer moving parts, easier to reason about and debug.
When stability and predictability matter most
CriticalWrite-Heavy Transactional Platform carries lower overall risk weight per the advisor's assessment.
When you want to minimise monitoring setup overhead
ModerateWrite-Heavy Transactional Platform has a lower observability burden: fewer watched metrics and monitoring targets.
When your architecture benefits from: write-heavy transactional workloads that emit downstream events (order placed, payment captured) benefit from the outbox pattern…
ModerateWrite-heavy transactional workloads that emit downstream events (order placed, payment captured) benefit from the outbox pattern to ensure events are published exactly when the database transaction commits: never before, never after. Key trade-off: Adds one INSERT per transaction to the outbox table: minor but nonzero write amplification. Operational note: Outbox table grows with write volume: implement TTL-based cleanup or partition pruning. Evidence: Payment processors like Stripe use outbox-style patterns to ensure webhook delivery matches transaction commits.
When your architecture benefits from: kafka is the standard downstream target for wal-based cdc pipelines: debezium captures database wal records and publishes them to…
ModerateKafka is the standard downstream target for WAL-based CDC pipelines: Debezium captures database WAL records and publishes them to Kafka topics, which downstream consumers process to maintain derived data stores, caches, and event-driven services. Key trade-off: Debezium replication slot holds WAL until consumed: disconnected Debezium can fill primary disk. Operational note: Debezium replication slot on PostgreSQL must be monitored: a lagging or disconnected Debezium causes replication slot WAL accumulation on the primary. Evidence: Debezium (Red Hat) captures PostgreSQL, MySQL, and MongoDB WAL and publishes to Kafka topics.
When your system requires decoupled async event processing
HighWrite-Heavy Transactional Platform includes event stream infrastructure (e.g., Kafka/Kinesis), enabling async decoupling between producers and consumers.
When to Avoid Each Scenario
Two-Sided Marketplace Platform
LeftWhen your team cannot mitigate: hot partition
HighThis architecture is significantly exposed to Hot Partition. One partition (a database shard, a Kafka topic partition, a Redis hash slot) receives traffic so far above its peers that it saturates while the others sit idle. Aggregate capacity looks healthy, but the hot partition throttles or lags, and everything routed to it degrades. The cause is skew in how keys map to partitions, and the fix depends on whether the skew is spread across many keys or concentrated in one.
When your team cannot mitigate: cascading failure
HighThis architecture is significantly exposed to Cascading Failure. A failure or degradation in one service causes increased load, held resources, or error propagation in its callers, which in turn degrade their callers, until the failure front propagates through the entire dependency graph and brings down services with no direct dependency on the original failure point.
When your team is early-stage or solo
HighTwo-Sided Marketplace Platform is rated 'advanced'. It requires experienced backend engineers or platform tooling to operate reliably at scale.
When you expect rapid growth within the next 12–18 months
ModerateThe advisor identifies 9 predicted bottlenecks for Two-Sided Marketplace Platform. Rapid growth will surface these limitations quickly.
Write-Heavy Transactional Platform
RightWhen your team cannot mitigate: write amplification cascade
HighThis architecture is significantly exposed to Write Amplification Cascade. Each logical application write triggers multiple physical writes through index maintenance, WAL generation, MVCC versioning, and replication, causing actual disk IOPS to exceed the provisioned I/O ceiling while the logical write rate appears modest.
When your team cannot mitigate: wal saturation
HighThis architecture is significantly exposed to WAL Saturation. PostgreSQL WAL (Write-Ahead Log) generation rate exceeds wal_buffers flush capacity or downstream replica/WAL archive bandwidth, causing write transactions to stall waiting for WAL flush and replication lag to grow unboundedly.
When your team is early-stage or solo
HighWrite-Heavy Transactional Platform is rated 'advanced'. It requires experienced backend engineers or platform tooling to operate reliably at scale.
When you expect rapid growth within the next 12–18 months
ModerateThe advisor identifies 7 predicted bottlenecks for Write-Heavy Transactional Platform. Rapid growth will surface these limitations quickly.
Team Fit
Solo developer or small startup
LeftTwo-Sided Marketplace Platform is more accessible for small teams. Fewer operational moving parts reduces on-call burden.
- ↳Validate that the simpler architecture can handle your projected load before committing.
Small product team (2–6 engineers)
LeftTwo-Sided Marketplace Platform suits small teams that need to move fast without deep platform tooling investment.
- ↳Consider Write-Heavy Transactional Platform only if your workload pattern specifically requires it.
Experienced backend team
DependsAn experienced team can operate either architecture. Choose based on workload fit, not team capability.
- ↳Prioritise alignment with existing infrastructure and tooling.
- ↳Write-Heavy Transactional Platform may require additional runbook coverage and alerting investment.
Platform engineering team or SRE-equipped organisation
RightA platform team can safely operate Write-Heavy Transactional Platform and will benefit from its more advanced scaling characteristics.
- ↳Ensure observability and alerting are configured before launch.
Migration Triggers
Migration Step 1
Both scenarios define a migration step at this stage. Two-Sided Marketplace Platform: triggered by 'Checkout failures from payment provider unavailability causi'. Write-Heavy Transactional Platform: triggered by 'Dual-write inconsistency events observed in production: DB w'.
Migration Step 2
Both scenarios define a migration step at this stage. Two-Sided Marketplace Platform: triggered by 'Listing search p99 > 1s; faceted navigation (category + pric'. Write-Heavy Transactional Platform: triggered by 'Primary write CPU > 70% sustained during peak windows; WAL v'.
Migration Step 3
Both scenarios define a migration step at this stage. Two-Sided Marketplace Platform: triggered by 'Domain teams stepping on each other's schema migrations; dat'. Write-Heavy Transactional Platform: triggered by 'Audit completeness requirements grow beyond point-in-time ba'.
Redis cache miss spike visible in monitoring; PostgreSQL query rate spiking for listing reads despite stable write volume; p99 listing API latency > 500ms during traffic spike events
Tier 1: Viral Listing Thundering Herd: Cache TTL expiry on hot listings during peak traffic: all concurrent requests bypass cache simultaneously. Recommended evolution: Implement staggered TTL jitter on listing cache entries; use probabilistic early refresh (refresh before TTL expiry when remaining TTL < 20% and request rate is high); implement single-flight/request coalescing at the application layer to collapse concurrent cache misses into a single database read .
Saga compensation events appearing in order event log; checkout p99 > 2s; pg_locks showing contended rows on inventory_reservations table; idempotency key conflicts increasing in payment service logs
Tier 2: Checkout Saga Contention: Concurrent checkout transactions competing for the same inventory rows; saga timeout thresholds too aggressive. Recommended evolution: Increase inventory reservation table partition count; tune saga step timeout to 2x the observed p99 for each step under load; implement a per-listing checkout serialization queue to prevent N concurrent sagas competing for the same inventory .
PgBouncer wait_queue > 0 sustained; application p99 write latency rising faster than PostgreSQL p99; pool_mode=transaction showing >80% utilization
Tier 1: Connection Pool Saturation: PgBouncer pool_size too small for write concurrency profile. Recommended evolution: Increase PgBouncer pool_size incrementally; profile transaction duration to right-size pool; consider separate pools for write-heavy and read-only workloads .
PostgreSQL checkpoint_completion_target warnings in logs; wal_buffers flushing more than once per second; pg_stat_bgwriter shows checkpoints_req rising; write p99 > 20ms without query explanation
Tier 2: WAL and Checkpoint Pressure: Write rate exceeding PostgreSQL's WAL flush and checkpoint throughput. Recommended evolution: Tune checkpoint_completion_target to 0.9; increase wal_buffers to 64MB; move PostgreSQL WAL to a dedicated NVMe volume separate from data directory .
Readiness Requirements
Apache Kafka: scenario has team_maturity below senior
BothKafka operational complexity requires dedicated expertise: consider MSK or Confluent Cloud to reduce ops burden
Required maturity: senior
Apache Kafka: scenario uses Kafka for event streaming or CDC
BothSet min.insync.replicas=2 with acks=all; monitor consumer lag as primary health signal
Required maturity: senior
Event stream operations expertise
BothThis architecture includes event stream infrastructure (Kafka, Kinesis, or similar). Operations requires consumer group management, partition assignment, dead-letter handling, and lag monitoring.
Required maturity: platform_engineering_team
PostgreSQL: scenario includes high_write_throughput or write_heavy workload
BothDeploy PgBouncer in transaction-mode pooling before relying on vertical scaling
Required maturity: mid_level
Runbooks and alerting for high-severity risks
Both5 high-severity risks identified. Each requires a documented runbook, alerting threshold, and on-call response procedure before running in production.
Cache sizing and eviction policy configuration
LeftRedis or equivalent cache requires correct maxmemory configuration, eviction policy selection (allkeys-lru is common), and cold-start warming strategy after restarts.
Elasticsearch: scenario has full_text_search or log_analytics workload
LeftConfigure ILM policies from day one to prevent shard explosion as data grows
Required maturity: senior
Elasticsearch: scenario uses Elasticsearch as a primary datastore
LeftElasticsearch is a search index, not a source of truth: add a durable primary store and sync to ES
Required maturity: senior
Elasticsearch: scenario uses dynamic mappings on high-cardinality fields
LeftDefine explicit index mappings: dynamic mapping on high-cardinality fields causes mapping explosions and cluster instability
Required maturity: senior
Minimum team maturity: Platform Engineering Team
LeftThis scenario has expert operational complexity. It is recommended for Platform Engineering Team teams or higher.
Required maturity: platform_engineering_team
RabbitMQ: scenario has high_throughput_writes exceeding 50k messages/second
LeftRabbitMQ throughput ceiling may be insufficient: evaluate Kafka for sustained high-throughput event streams
Required maturity: mid_level
RabbitMQ: scenario requires event replay or consumer catch-up from historical messages
LeftRabbitMQ deletes acknowledged messages: use Kafka for replay-capable event streaming
Required maturity: mid_level
RabbitMQ: scenario uses classic mirrored queues for HA
LeftMigrate to quorum queues: classic mirrored queues have known split-brain behavior under network partition
Required maturity: mid_level
Redis: scenario has read_heavy workload with high cache miss risk
LeftImplement cache stampede protection (probabilistic early expiry or locking) to prevent thundering herd on cold start
Required maturity: junior
Redis: scenario relies on Redis for data that cannot be re-derived
LeftRedis is not a durable store: add persistence layer or treat Redis as expendable cache only
Required maturity: junior
Minimum team maturity: Experienced Backend Team
RightThis scenario has high operational complexity. It is recommended for Experienced Backend Team teams or higher.
Required maturity: experienced_backend_team
Replica lag monitoring and lag-aware routing
RightRead replicas must be monitored for replication lag. The application router must include a max_lag_ms threshold; queries above that threshold must be redirected to the primary.
Generator Constraints
Two-Sided Marketplace Platform
LeftGenerator relevance documented but not yet production-ready.
For marketplace product briefs, the generator must produce the full event-driven composition: API gateway → domain services → outbox → Kafka → downstream consumers. Saga orchestration templates for the checkout flow (create_order → reserve_inventory → charge_payment → notify_seller) must be generated with explicit compensation paths. The notification subsystem (RabbitMQ + dead-letter queue) must be generated as a separate deployable unit with its own operational SLA.
Write-Heavy Transactional Platform
RightGenerator relevance documented but not yet production-ready.
For write-heavy product briefs requiring ACID guarantees and event durability, the generator should propose the PostgreSQL + outbox + WAL CDC + Kafka composition as the canonical starting point. Dual-write (synchronous DB + Kafka publish) must be listed as an anti-pattern with explicit consistency hazard documentation. PgBouncer must be included by default: not as an optional enhancement.
Supporting Evidence
| Type | Reference | Explanation |
|---|---|---|
| Comparison | compare_marketplace_platform_vs_write_heavy_transactional_platform | Full comparison of Two-Sided Marketplace Platform vs Write-Heavy Transactional Platform: 6 dimensions, 4 shared components, 1 shared risks. |
| Advisor | advisor_marketplace_platform | Advisor for Two-Sided Marketplace Platform: 0 strengths, 5 risks, maturity: advanced. |
| Advisor | advisor_write_heavy_transactional_platform | Advisor for Write-Heavy Transactional Platform: 2 strengths, 4 risks, maturity: advanced. |
| Scenario | marketplace_platform | Scenario 'Two-Sided Marketplace Platform': 4 scaling thresholds, 3 migration paths, complexity: expert. |
| Scenario | write_heavy_transactional_platform | Scenario 'Write-Heavy Transactional Platform': 4 scaling thresholds, 3 migration paths, complexity: high. |
| Risk Path | prop_workload_profile_marketplace_mixed_workload_risk_hot_partition | Marketplace Mixed → Hot Partition |
| Risk Path | prop_technology_profile_redis_risk_thundering_herd | Redis → Thundering Herd (Cache Stampede) |
| Risk Path | prop_workload_profile_write_heavy_transactional_risk_wal_saturation | Write-Heavy Transactional → WAL Saturation |
| Risk Path | prop_workload_profile_write_heavy_transactional_risk_lock_contention | Write-Heavy Transactional → Lock Contention |
| Risk Path | prop_workload_profile_marketplace_mixed_workload_risk_hot_partition | Referenced by the operational risk comparison dimension. |
| Risk Path | prop_technology_profile_redis_risk_thundering_herd | Referenced by the operational risk comparison dimension. |
Limitations
- ·Decision guidance is grounded in YAML knowledge only. Not measured from any production system.
- ·Recommendations are deterministic heuristics based on structured knowledge. Your specific workload, team profile, and business context may lead to different conclusions.
- ·Generator constraints are preliminary. No scenario should be treated as production generation-ready at this stage.
Comparison complete
Profile, topology, simulation, advisor, comparison, and decision path are ready. Your architecture decision is grounded in structured knowledge and deterministic reasoning.