DBRavenArchitecture Decision Reports

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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

AI / RAG

API Gateway Platform

Multi-Tenant SaaS

Analytics Data Platform

Analytics

Audit and Compliance Platform

Financial Ledger

Content Management Platform

Read-Heavy

Developer Tools Platform

Multi-Tenant SaaS

Distributed Job Queue Platform

Write-Heavy

E-Commerce Order Platform

Marketplace

Event-Driven Analytics Pipeline

Event-Driven

Financial Ledger Platform

Financial Ledger

Gaming Backend Platform

Realtime Collab

Geospatial Tracking Platform

Realtime Collab

Healthcare Records Platform

Financial Ledger

IoT Telemetry Ingestion Platform

Write-Heavy

ML Feature Serving Platform

AI / RAG

Multi-Tenant SaaS Platform

Multi-Tenant SaaS

Notification Delivery Platform

Event-Driven

Observability Platform

Analytics

Read-Heavy SaaS API

Read-Heavy

Realtime Collaborative Editor

Realtime Collab

Search-Heavy Content Platform

Search-Heavy

Social Feed Platform

Event-Driven

Streaming Media Platform

Event-Driven

Two-Sided Marketplace Platform

Marketplace

Write-Heavy Transactional Platform

right, removals (−)

AI Retrieval-Augmented Generation Platform

AI / RAG

API Gateway Platform

Multi-Tenant SaaS

Analytics Data Platform

Audit and Compliance Platform

Financial Ledger

Content Management Platform

Read-Heavy

Developer Tools Platform

Multi-Tenant SaaS

Distributed Job Queue Platform

Write-Heavy

E-Commerce Order Platform

Marketplace

Event-Driven Analytics Pipeline

Event-Driven

Financial Ledger Platform

Financial Ledger

Gaming Backend Platform

Realtime Collab

Geospatial Tracking Platform

Realtime Collab

Healthcare Records Platform

Financial Ledger

IoT Telemetry Ingestion Platform

Write-Heavy

ML Feature Serving Platform

AI / RAG

Multi-Tenant SaaS Platform

Multi-Tenant SaaS

Notification Delivery Platform

Event-Driven

Observability Platform

Analytics

Read-Heavy SaaS API

Read-Heavy

Realtime Collaborative Editor

Realtime Collab

Search-Heavy Content Platform

Search-Heavy

Social Feed Platform

Event-Driven

Streaming Media Platform

Event-Driven

Two-Sided Marketplace Platform

Marketplace

Write-Heavy Transactional Platform

Write-Heavy

Analytics Data Platform→Write-Heavy Transactional Platform

−10 removed+11 added4 unchanged

Components

11

Analytics Data Platform

11

Write-Heavy Transactional Platform

4 shared−7+7

Failure Modes

3

Analytics Data Platform

4

Write-Heavy Transactional Platform

0 shared−3+4

Connections

5

Analytics Data Platform

5

Write-Heavy Transactional Platform

1 shared−4+4

Components

4 shared−7 left only+7 right only

=

High-Throughput OLTPworkload

workload

=

PostgreSQLprimary datastore

data management

=

Apache Kafkaevent stream

async processing

=

Change Data Capture via WALarchitecture pattern

application logic

−

Analytics Heavy (OLAP)workload

workload

−

ClickHouseprimary datastore

data management

−

CQRS (Command Query Responsibility Segregation)architecture pattern

application logic

−

Materialized Viewarchitecture pattern

application logic

−

Queue Backlog Accumulationoperational risk

operational risk

−

Hot Partitionoperational risk

operational risk

−

Slow Consumeroperational risk

operational risk

+

Write-Heavy Transactionalworkload

workload

+

Transactional Outbox Patternarchitecture pattern

application logic

+

Connection Poolingarchitecture pattern

interface or access

+

Write Amplification Cascadeoperational risk

operational risk

+

WAL Saturationoperational risk

operational risk

+

Lock Contentionoperational risk

operational risk

+

Checkpoint Amplificationoperational risk

operational risk

Failure Modes

−3 left only+4 right only

−

Queue Backlog Accumulation1 nodes affected

highhigh

−

Hot Partition0 nodes affected

highhigh

−

Slow Consumer0 nodes affected

moderate

+

Write Amplification Cascade0 nodes affected

highhigh

+

WAL Saturation1 nodes affected

highhigh

+

Lock Contention1 nodes affected

highhigh

+

Checkpoint Amplification1 nodes affected

moderate

Connections

1 shared−4 left only+4 right only

=

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

−

ClickHouse's columnar storage engine, vectorized query execution, and MergeTree family of table engines are specifically designed for analytics-heavy workloads: high-throughput aggregations over billions of rows with sub-second query latency.

supports

−

Analytics-heavy workloads pre-compute expensive aggregations and joins into materialized views, reducing repeated full-scan query cost from minutes per query to milliseconds per lookup.

benefits from

−

CQRS separates the write model (normalized, ACID) from the read model; materialized views implement the read model by pre-computing the denormalized view that the query side serves. Each pattern makes the other more operationally tractable.

complements

−

A slow consumer processing messages below the producer rate causes queue backlog to accumulate. If processing speed does not recover, backlog grows unboundedly, eventually causing either message loss (if the queue has a depth limit) or indefinite processing delay.

introduces riskrisk path

+

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

+

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, 11 nodes, 5 edges, 3 risks, 1 simulation seeds

Complexity

← Analytics

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

3 risks (top: high), 2 high/critical, 0 confirmed by simulation

Operational Risk

← Analytics

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

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

Scalability

depends

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

Advisor assessment: Advanced; recommended team: Experienced Backend Team; 9 operational requirements

Operational Maturity

tie

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

4 watched metrics, 3 observability recommendations, 1 simulation seeds

Observability

← Analytics

6 watched metrics, 4 observability recommendations, 3 simulation seeds

generator relevance documented; topology generation relevance noted; simulation relevance noted; 1 seeds with generator notes

Generator Readiness

Write-Heavy →

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

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