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 (−)

Streaming Media PlatformRealtime Collaborative Editor
25 removed+4 added2 unchanged

Components

21

Streaming Media Platform

5

Realtime Collaborative Editor

2 shared19+3

Failure Modes

6

Streaming Media Platform

1

Realtime Collaborative Editor

0 shared6+1

Connections

0

Streaming Media Platform

2

Realtime Collaborative Editor

0 shared+2

Components

2 shared19 left only+3 right only
=
PostgreSQLprimary datastore
data management
=
Rediscache
acceleration
Event Streamingworkload
workload
Batch ETL Pipelineworkload
workload
Read-Heavy API Backendworkload
workload
Time-Series Metricsworkload
workload
Apache Kafkaevent stream
async processing
Apache Cassandraprimary datastore
data management
MinIOsupporting component
application logic
Competing Consumersarchitecture pattern
application logic
Cache-Asidearchitecture pattern
application logic
Event Sourcingarchitecture pattern
application logic
Change Data Capture via WALarchitecture pattern
application logic
Backpressurearchitecture pattern
application logic
Rate Limitingarchitecture pattern
application logic
Queue Backlog Accumulationoperational risk
operational risk
Thundering Herd (Cache Stampede)operational risk
operational risk
Disk I/O Saturationoperational risk
operational risk
Slow Consumeroperational risk
operational risk
Hot Partitionoperational risk
operational risk
Cascading Failureoperational risk
operational risk
+
High-Throughput OLTPworkload
workload
+
Connection Poolingarchitecture pattern
interface or access
+
Connection Pool Exhaustionoperational risk
operational risk

Failure Modes

6 left only+1 right only
Queue Backlog Accumulation2 nodes affected
highhigh
Thundering Herd (Cache Stampede)1 nodes affected
highhigh
Disk I/O Saturation1 nodes affected
highhigh
Slow Consumer0 nodes affected
moderate
Hot Partition0 nodes affected
highhigh
Cascading Failure0 nodes affected
highhigh
+
Connection Pool Exhaustion1 nodes affected
highhigh

Connections

+2 right only
+
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 clients hold persistent TCP connections per thread or goroutine. Under connection pool misconfiguration or sudden traffic spikes, the Redis server can exhaust its maxclients limit, causing cascading cache misses that amplify load on the primary database.
introduces riskrisk path

Six-Dimension Assessment

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

high complexity, 21 nodes, 0 edges, 6 risks, 3 simulation seeds

Complexity

Realtime →

expert complexity, 5 nodes, 2 edges, 1 risks, 1 simulation seeds

6 risks (top: high), 5 high/critical, 0 confirmed by simulation

Operational Risk

Realtime →

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

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

Scalability

← Streaming

3 scaling thresholds, 2 migration paths, 6 advisor scaling signals

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

Operational Maturity

← Streaming

Advisor assessment: Expert Only; recommended team: Enterprise Architecture Team; 6 operational requirements

8 watched metrics, 7 observability recommendations, 3 simulation seeds

Observability

Realtime →

4 watched metrics, 2 observability recommendations, 1 simulation seeds

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

Generator Readiness

← Streaming

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