Agentic AI Atlasby a5c.ai
OverviewWikiGraphFor AgentsEdgesSearchWorkspace
/
GitHubDocsDiscord
iiRecord
Agentic AI Atlas · CQRS Read Model (TypeScript, Elasticsearch, Kafka, PostgreSQL, NestJS, Docker)
stack-profile:cqrs-read-modela5c.ai
Search record views/
Record · tabs

Available views

II.Record viewspp. 1 - 1
overviewjsongraph
II.
StackProfile overview

stack-profile:cqrs-read-model

Reference · live

CQRS Read Model (TypeScript, Elasticsearch, Kafka, PostgreSQL, NestJS, Docker) overview

A CQRS (Command Query Responsibility Segregation) implementation where the write side persists events and aggregates in PostgreSQL through NestJS command handlers, while a separate read side projects denormalized views into Elasticsearch for fast, flexible querying. Kafka transports domain events from the write side to read-model projectors, which build optimized search indices and materialized views. TypeScript ensures type safety across both sides of the CQRS boundary. Docker Compose orchestrates PostgreSQL, Kafka, Elasticsearch, and the application services for local development. The tradeoff is eventual consistency between write and read models and the operational burden of running Kafka and Elasticsearch, but the pattern unlocks independent scaling and optimization of reads and writes.

StackProfileOutgoing · 20Incoming · 0

Attributes

displayName
CQRS Read Model (TypeScript, Elasticsearch, Kafka, PostgreSQL, NestJS, Docker)
description
A CQRS (Command Query Responsibility Segregation) implementation where the write side persists events and aggregates in PostgreSQL through NestJS command handlers, while a separate read side projects denormalized views into Elasticsearch for fast, flexible querying. Kafka transports domain events from the write side to read-model projectors, which build optimized search indices and materialized views. TypeScript ensures type safety across both sides of the CQRS boundary. Docker Compose orchestrates PostgreSQL, Kafka, Elasticsearch, and the application services for local development. The tradeoff is eventual consistency between write and read models and the operational burden of running Kafka and Elasticsearch, but the pattern unlocks independent scaling and optimization of reads and writes.
composes
  • language:typescript
  • framework:nestjs
  • tool:elasticsearch
  • library:prisma
  • library:ioredis
  • library:bullmq
  • tool:docker
  • tool:docker-compose

Outgoing edges

applies_to2
  • domain:backend·DomainBackend
  • domain:software-engineering·DomainSoftware Engineering
composed_of8
  • language:typescript·LanguageTypeScript
  • framework:nestjs·FrameworkNestJS
  • tool:elasticsearch·ToolElasticsearch
  • library:prisma·LibraryPrisma
  • library:ioredis·Libraryioredis
  • library:bullmq·LibraryBullMQ
  • tool:docker·ToolDocker
  • tool:docker-compose·ToolDocker Compose
follows_workflow2
  • workflow:event-driven-architecture-review·WorkflowEvent-Driven Architecture Review
  • workflow:event-storming-session·WorkflowEvent Storming Session
requires_skill_area5
  • skill-area:cqrs·SkillAreaCQRS
  • skill-area:event-sourcing·SkillAreaEvent Sourcing
  • skill-area:search-indexing·SkillAreaSearch and Indexing
  • skill-area:kafka-stream-processing·SkillAreaKafka Stream Processing
  • skill-area:streaming-realtime-processing·SkillAreaStreaming and Real-time Processing
used_by_role3
  • role:backend-engineer·RoleBackend Engineer
  • role:architect·RoleArchitect
  • role:data-engineer·RoleData Engineer

Incoming edges

None.

Related pages

No related wiki pages for this record.

Shortcuts

Open in graph
Browse node kind