DBRaven

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 (−)

right, removals (−)

Event-Driven Analytics PipelineML Feature Serving Platform
4 removed+25 added2 unchanged

Components

5

Event-Driven Analytics Pipeline

21

ML Feature Serving Platform

2 shared3+19

Failure Modes

1

Event-Driven Analytics Pipeline

6

ML Feature Serving Platform

0 shared1+6

Connections

0

Event-Driven Analytics Pipeline

0

ML Feature Serving Platform

0 shared

Components

2 shared3 left only+19 right only
=
PostgreSQLprimary datastore
data management
=
Apache Kafkaevent stream
async processing
High-Throughput OLTPworkload
workload
Change Data Capture via WALarchitecture pattern
application logic
Replication Lag Cascadeoperational risk
operational risk
+
AI Embedding Lookupworkload
workload
+
Read-Heavy API Backendworkload
workload
+
Analytics Heavy (OLAP)workload
workload
+
Rediscache
acceleration
+
Qdrantsupporting component
application logic
+
Apache Cassandraprimary datastore
data management
+
ClickHouseprimary datastore
data management
+
Cache-Asidearchitecture pattern
application logic
+
Read-Through Cachearchitecture pattern
application logic
+
Materialized Viewarchitecture pattern
application logic
+
Vector Similarity Searcharchitecture pattern
application logic
+
Competing Consumersarchitecture pattern
application logic
+
CQRS (Command Query Responsibility Segregation)architecture pattern
application logic
+
Embedding Driftoperational risk
operational risk
+
Stale Vector Indexoperational risk
operational risk
+
Cold Start Latencyoperational risk
operational risk
+
Cache Stampede (Dog-Pile)operational risk
operational risk
+
Read Amplification (LSM Tree)operational risk
operational risk
+
Slow Consumeroperational risk
operational risk

Failure Modes

1 left only+6 right only
Replication Lag Cascade0 nodes affected
moderate
+
Embedding Drift3 nodes affected
highhigh
+
Stale Vector Index1 nodes affected
moderate
+
Cold Start Latency0 nodes affected
low
+
Cache Stampede (Dog-Pile)1 nodes affected
highhigh
+
Read Amplification (LSM Tree)1 nodes affected
highhigh
+
Slow Consumer0 nodes affected
moderate

Connections

Six-Dimension Assessment

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

high complexity, 5 nodes, 0 edges, 1 risks, 0 simulation seeds

Complexity

← Event-Driven

expert complexity, 21 nodes, 0 edges, 6 risks, 4 simulation seeds

1 risks (top: moderate), 0 high/critical, 0 confirmed by simulation

Operational Risk

← Event-Driven

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

3 scaling thresholds, 2 migration paths, 3 advisor scaling signals

Scalability

ML →

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

Advisor assessment: Advanced; recommended team: Experienced Backend Team; 5 operational requirements

Operational Maturity

tie

Advisor assessment: Advanced; recommended team: Platform Engineering Team; 15 operational requirements

0 watched metrics, 0 observability recommendations, 0 simulation seeds

Observability

← Event-Driven

8 watched metrics, 4 observability recommendations, 4 simulation seeds

generator relevance documented; topology generation relevance noted; simulation relevance noted

Generator Readiness

ML →

generator relevance documented; topology generation relevance noted; simulation relevance noted; 4 seeds with generator notes