DBRavenArchitecture Decision Reports

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

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

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

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

Read-Heavy SaaS API→Search-Heavy Content Platform

−4 removed+12 added5 unchanged

Components

7

Read-Heavy SaaS API

13

Search-Heavy Content Platform

4 shared−3+9

Failure Modes

2

Read-Heavy SaaS API

4

Search-Heavy Content Platform

1 shared−1+3

Connections

6

Read-Heavy SaaS API

6

Search-Heavy Content Platform

2 shared−4+4

Components

4 shared−3 left only+9 right only

=

Read-Heavy API Backendworkload

workload

=

PostgreSQLprimary datastore

data management

=

Rediscache

acceleration

=

Replication Lag Cascadeoperational risk

operational risk

−

Connection Poolingarchitecture pattern

interface or access

−

Read Replicaarchitecture pattern

application logic

−

Connection Pool Exhaustionoperational risk

operational risk

+

Search Heavyworkload

workload

+

Elasticsearchsupporting component

application logic

+

Change Data Capture via WALarchitecture pattern

application logic

+

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

+

Thundering Herd (Cache Stampede)operational risk

operational risk

Failure Modes

1 shared−1 left only+3 right only

=

Replication Lag Cascade1 nodes affected

moderate

−

Connection Pool Exhaustion1 nodes affected

highhigh

+

Table and Index Bloat0 nodes affected

moderate

+

Hot Partition0 nodes affected

highhigh

+

Thundering Herd (Cache Stampede)1 nodes affected

highhigh

Connections

2 shared−4 left only+4 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

−

Read-heavy APIs generate large numbers of short-lived database connections. Connection pooling reduces per-request connection overhead and allows the database to serve far more concurrent requests than its max_connections limit.

benefits from

−

PostgreSQL's built-in streaming replication provides the replication substrate that makes the read replica pattern operational. Physical and logical replication are both supported, enabling read scaling without data modification.

supports

−

The read replica pattern is structurally vulnerable to replication lag cascade because its value proposition: serving reads from replicas: depends on replica data being sufficiently current. Any condition that delays WAL replay degrades or invalidates the replica's usefulness.

vulnerable torisk path

−

A connection pool bounds the total database connections an application can open, preventing connection storms during traffic spikes and protecting the database server from exceeding its connection limit.

mitigates

+

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

Six-Dimension Assessment

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

moderate complexity, 7 nodes, 6 edges, 2 risks, 2 simulation seeds

Complexity

← Read-Heavy

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

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

Operational Risk

← Read-Heavy

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

4 scaling thresholds, 2 migration paths, 9 advisor scaling signals

Scalability

← Read-Heavy

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

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

Operational Maturity

tie

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

8 watched metrics, 3 observability recommendations, 2 simulation seeds

Observability

Search-Heavy →

2 watched metrics, 3 observability recommendations, 1 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; 1 seeds with generator notes

Full comparison + decision path →Topology: Read-Heavy SaaS API →Topology: Search-Heavy Content Platform →