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

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

Social Feed Platform

Event-Driven

Streaming Media Platform

Event-Driven

Two-Sided Marketplace Platform

Marketplace

Write-Heavy Transactional Platform

Write-Heavy

Search-Heavy Content Platform→Write-Heavy Transactional Platform

−15 removed+13 added2 unchanged

Components

13

Search-Heavy Content Platform

11

Write-Heavy Transactional Platform

2 shared−11+9

Failure Modes

4

Search-Heavy Content Platform

4

Write-Heavy Transactional Platform

0 shared−4+4

Connections

6

Search-Heavy Content Platform

5

Write-Heavy Transactional Platform

0 shared−6+5

Components

2 shared−11 left only+9 right only

=

PostgreSQLprimary datastore

data management

=

Change Data Capture via WALarchitecture pattern

application logic

−

Search Heavyworkload

workload

−

Read-Heavy API Backendworkload

workload

−

Elasticsearchsupporting component

application logic

−

Rediscache

acceleration

−

CQRS (Command Query Responsibility Segregation)architecture pattern

application logic

−

Cache-Asidearchitecture pattern

application logic

−

Materialized Viewarchitecture pattern

application logic

−

Table and Index Bloatoperational risk

operational risk

−

Hot Partitionoperational risk

operational risk

−

Replication Lag Cascadeoperational risk

operational risk

−

Thundering Herd (Cache Stampede)operational risk

operational risk

+

Write-Heavy Transactionalworkload

workload

+

High-Throughput OLTPworkload

workload

+

Apache Kafkaevent stream

async processing

+

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

−4 left only+4 right only

−

Table and Index Bloat0 nodes affected

moderate

−

Hot Partition0 nodes affected

highhigh

−

Replication Lag Cascade0 nodes affected

moderate

−

Thundering Herd (Cache Stampede)1 nodes affected

highhigh

+

Write Amplification Cascade0 nodes affected

highhigh

+

WAL Saturation1 nodes affected

highhigh

+

Lock Contention1 nodes affected

highhigh

+

Checkpoint Amplification1 nodes affected

moderate

Connections

−6 left only+5 right only

−

Redis caching absorbs repeated read requests at the edge, reducing database load and latency for high read-to-write ratio workloads by orders of magnitude.

mitigates

−

Read-heavy APIs benefit directly from Redis as a caching tier that absorbs repeated identical reads and provides sub-millisecond response times for hot data, reducing both latency and database load.

benefits from

−

Redis distributed locks (via SET NX EX or Redlock) prevent thundering herd by ensuring only one caller repopulates a cache entry at a time, with other callers either waiting or returning a stale value until the cache is warm.

mitigates

−

Search-heavy workloads cache popular queries and their result sets, absorbing the majority of search traffic from cache and reserving Elasticsearch or other search backends for uncached or freshness-sensitive queries.

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

−

Redis is itself vulnerable to thundering herd when it restarts or flushes: all cache entries expire simultaneously, and many concurrent requests all miss and race to repopulate the same keys from the database, causing a stampede that can overwhelm the downstream database.

vulnerable torisk 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

+

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, 13 nodes, 6 edges, 4 risks, 1 simulation seeds

Complexity

Write-Heavy →

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

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

Operational Risk

← Search-Heavy

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: Intermediate; recommended team: Experienced Backend Team; 9 operational requirements

Operational Maturity

← Search-Heavy

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

2 watched metrics, 3 observability recommendations, 1 simulation seeds

Observability

← Search-Heavy

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: Search-Heavy Content Platform →Topology: Write-Heavy Transactional Platform →