DBRaven
Start Review →

Architecture Structural Diff

Compare two scenarios node-by-node. See exactly which components, failure modes, and connections are shared, removed (−), or added (+) when switching from the left scenario to the right.

Select Scenarios to Diff

left, removals (−)

AI Retrieval-Augmented Generation Platform
high

AI / RAG

API Gateway Platform
high

Multi-Tenant SaaS

Analytics Data Platform
high

Analytics

Audit and Compliance Platform
high

Financial Ledger

Content Management Platform
moderate

Read-Heavy

Developer Tools Platform
high

Multi-Tenant SaaS

Distributed Job Queue Platform
moderate

Write-Heavy

E-Commerce Order Platform
high

Marketplace

Event-Driven Analytics Pipeline
high

Event-Driven

Financial Ledger Platform
expert

Financial Ledger

Gaming Backend Platform
high

Realtime Collab

Geospatial Tracking Platform
high

Realtime Collab

Healthcare Records Platform
expert

Financial Ledger

IoT Telemetry Ingestion Platform
high

Write-Heavy

ML Feature Serving Platform
expert

AI / RAG

Multi-Tenant SaaS Platform
moderate

Multi-Tenant SaaS

Notification Delivery Platform
moderate

Event-Driven

Observability Platform
high✓

Analytics

Read-Heavy SaaS API
moderate

Read-Heavy

Realtime Collaborative Editor
expert

Realtime Collab

Search-Heavy Content Platform
high

Search-Heavy

Social Feed Platform
high

Event-Driven

Streaming Media Platform
high

Event-Driven

Two-Sided Marketplace Platform
expert

Marketplace

Write-Heavy Transactional Platform

right, removals (−)

AI Retrieval-Augmented Generation Platform
high

AI / RAG

API Gateway Platform
high

Multi-Tenant SaaS

Analytics Data Platform
high

Analytics

Audit and Compliance Platform
high

Financial Ledger

Content Management Platform
moderate

Read-Heavy

Developer Tools Platform
high

Multi-Tenant SaaS

Distributed Job Queue Platform
moderate

Write-Heavy

E-Commerce Order Platform
high

Marketplace

Event-Driven Analytics Pipeline
high

Event-Driven

Financial Ledger Platform
expert

Financial Ledger

Gaming Backend Platform
high

Realtime Collab

Geospatial Tracking Platform
high

Realtime Collab

Healthcare Records Platform
expert

Financial Ledger

IoT Telemetry Ingestion Platform
high

Write-Heavy

ML Feature Serving Platform
expert

AI / RAG

Multi-Tenant SaaS Platform
moderate

Multi-Tenant SaaS

Notification Delivery Platform
moderate

Event-Driven

Observability Platform
Read-Heavy SaaS API
moderate

Read-Heavy

Realtime Collaborative Editor
expert

Realtime Collab

Search-Heavy Content Platform
high

Search-Heavy

Social Feed Platform
high

Event-Driven

Streaming Media Platform
high

Event-Driven

Two-Sided Marketplace Platform
expert

Marketplace

Write-Heavy Transactional Platform
high✓

Write-Heavy

Observability Platform→Write-Heavy Transactional Platform
−20 removed+8 added7 unchanged

Components

21

Observability Platform

11

Write-Heavy Transactional Platform

5 shared−16+6

Failure Modes

6

Observability Platform

4

Write-Heavy Transactional Platform

2 shared−4+2

Connections

0

Observability Platform

5

Write-Heavy Transactional Platform

0 shared+5

Components

5 shared−16 left only+6 right only
=
Write-Heavy Transactionalworkload
workload
=
Apache Kafkaevent stream
async processing
=
Change Data Capture via WALarchitecture pattern
application logic
=
WAL Saturationoperational risk
operational risk
=
Write Amplification Cascadeoperational risk
operational risk
−
Analytics Heavy (OLAP)workload
workload
−
Time-Series Metricsworkload
workload
−
Event Streamingworkload
workload
−
ClickHouseprimary datastore
data management
−
Elasticsearchsupporting component
application logic
−
TimescaleDBsupporting component
application logic
−
Rediscache
acceleration
−
Time Series Rolluparchitecture pattern
application logic
−
Competing Consumersarchitecture pattern
application logic
−
Materialized Viewarchitecture pattern
application logic
−
Backpressurearchitecture pattern
application logic
−
Rate Limitingarchitecture pattern
application logic
−
Disk I/O Saturationoperational risk
operational risk
−
Hot Partitionoperational risk
operational risk
−
Slow Consumeroperational risk
operational risk
−
Fanout Amplificationoperational risk
operational risk
+
High-Throughput OLTPworkload
workload
+
PostgreSQLprimary datastore
data management
+
Transactional Outbox Patternarchitecture pattern
application logic
+
Connection Poolingarchitecture pattern
interface or access
+
Lock Contentionoperational risk
operational risk
+
Checkpoint Amplificationoperational risk
operational risk

Failure Modes

2 shared−4 left only+2 right only
=
WAL Saturation1 nodes affected
high
=
Write Amplification Cascade0 nodes affected
high
−
Disk I/O Saturation1 nodes affected
highhigh
−
Hot Partition0 nodes affected
highhigh
−
Slow Consumer0 nodes affected
moderate
−
Fanout Amplification0 nodes affected
moderate
+
Lock Contention1 nodes affected
highhigh
+
Checkpoint Amplification1 nodes affected
moderate

Connections

+5 right only
+
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.
benefits from
+
Kafka 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.
supports
+
Write-heavy transactional workloads trigger frequent PostgreSQL checkpoints that flush large numbers of dirty pages to disk simultaneously, causing I/O spikes that interrupt query execution and increase write amplification beyond the WAL baseline.
vulnerable torisk path
+
Write-heavy transactional workloads amplify lock contention: many concurrent writers contend for row-level locks on the same records (e.g., shared account balances, inventory counts), causing transactions to queue, latency to spike, and throughput to plateau well below hardware limits.
vulnerable torisk path
+
Write-heavy transactional workloads generate high WAL volume that can saturate WAL writer throughput, fill the WAL buffer, and: in the extreme: cause write transactions to block waiting for WAL to be flushed to disk or consumed by replicas.
vulnerable torisk path

Six-Dimension Assessment

Structural comparison across complexity, risk, scalability, maturity, observability, and generator readiness.

high complexity, 21 nodes, 0 edges, 6 risks, 2 simulation seeds

Complexity

Write-Heavy →

high complexity, 11 nodes, 5 edges, 4 risks, 3 simulation seeds

6 risks (top: high), 4 high/critical, 0 confirmed by simulation

Operational Risk

Write-Heavy →

4 risks (top: high), 3 high/critical, 0 confirmed by simulation

4 scaling thresholds, 3 migration paths, 4 advisor scaling signals

Scalability

← Observability

4 scaling thresholds, 3 migration paths, 4 advisor scaling signals

Advisor assessment: Advanced; recommended team: Experienced Backend Team; 14 operational requirements

Operational Maturity

tie

Advisor assessment: Advanced; recommended team: Experienced Backend Team; 7 operational requirements

4 watched metrics, 5 observability recommendations, 2 simulation seeds

Observability

tie

6 watched metrics, 4 observability recommendations, 3 simulation seeds

generator relevance documented; topology generation relevance noted; simulation relevance noted; 2 seeds with generator notes

Generator Readiness

depends

generator relevance documented; topology generation relevance noted; simulation relevance noted; 3 seeds with generator notes

Full comparison + decision path →Topology: Observability Platform →Topology: Write-Heavy Transactional Platform →