tech-matrix

name	tech-matrix
description	Reference document for monopoly tech-matrix.
category	Document Processing
source	antigravity
tags	["node","api","ai","workflow","design","document","docker","kubernetes","aws","gcp"]
url	https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/monopoly/tech-matrix

MONOPOLY — Technology Decision Matrix

Table of Contents

1. Database Selection
2. Cache Selection
3. Message Queue / Event Streaming
4. API Protocol
5. Search Engine
6. Object Storage
7. Container Orchestration
8. Load Balancer
9. Observability Stack
10. CDN

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1. Database Selection

Relational (SQL)

Database	Best For	Avoid When	Scale Ceiling
PostgreSQL	Complex queries, JSONB, GIS, strong consistency, most default use cases	Ultra-high write throughput (>100K writes/s)	~10TB single node; use Citus for horizontal
MySQL / MariaDB	Read-heavy apps, legacy systems, WordPress/Drupal ecosystem	Complex queries, full ACID at scale	~10TB; use Vitess for sharding
CockroachDB	Global distributed SQL, geo-partitioning, multi-region	Simple single-region apps (overkill)	Petabyte-scale
PlanetScale	MySQL-compatible, serverless, branch-based workflow	Complex JOINs (foreign keys removed by design)	Very high — Vitess based
Amazon Aurora	AWS-native apps, managed PostgreSQL/MySQL, high availability	Non-AWS environments	Up to 128TB, 15 replicas

NoSQL

Database	Best For	Avoid When	Scale Ceiling
MongoDB	Flexible schema, document model, prototyping	Financial transactions requiring ACID	Petabyte-scale with sharding
DynamoDB	Key-value at massive scale, AWS-native, serverless, predictable latency	Complex queries, ad-hoc analytics, JOINs	Unlimited (AWS-managed)
Cassandra	Write-heavy, time-series, wide-column, geographically distributed	Read-heavy with complex queries	Petabyte-scale; used at Apple, Netflix
Redis	Cache, sessions, leaderboards, pub/sub, rate limiting	Primary data store for complex models	~1TB per node; cluster for more
Elasticsearch	Full-text search, log aggregation, analytics	Primary database (durability risk)	Petabyte-scale with clusters
InfluxDB	Time-series metrics, IoT, monitoring data	General-purpose data	Very high write throughput
Neo4j	Graph data, social networks, recommendation engines, fraud detection	Non-graph data (overhead not worth it)	Billions of nodes

Decision Framework

Is your data relational (joins, foreign keys, transactions)?
  YES → Start with PostgreSQL
  NO  → Continue below

Is your primary access pattern key-value?
  YES, need extreme scale → DynamoDB or Cassandra
  YES, need speed/cache → Redis

Is your data document-shaped (nested, flexible schema)?
  YES → MongoDB

Is it time-series (metrics, logs, IoT)?
  YES → InfluxDB or TimescaleDB

Is it graph (relationships are the data)?
  YES → Neo4j

Is it search?
  YES → Elasticsearch / OpenSearch

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2. Cache Selection

Technology	Best For	Max Single Node	Cluster Support
Redis	Sessions, leaderboards, pub/sub, complex data structures, Lua scripting	~1TB RAM	Yes (Redis Cluster, Redis Sentinel)
Memcached	Simple key-value, multi-threaded, large object cache	~64GB RAM	Yes (client-side sharding)
Varnish	HTTP reverse proxy cache, full-page caching	RAM bound	Limited
CloudFront / CDN	Static assets, edge caching globally	N/A (distributed)	Built-in global distribution

Default recommendation: Redis — more features, better ecosystem, active development.

Use Memcached only when: you need multi-threading for CPU-bound caching workloads and don't need data structures beyond string.

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3. Message Queue / Event Streaming

Technology	Model	Best For	Throughput	Retention
Apache Kafka	Log-based streaming	Event sourcing, high-throughput pipelines, replay, audit	Millions msg/s	Days to forever
RabbitMQ	AMQP message broker	Task queues, RPC, routing, fanout	50K–100K msg/s	Until consumed
AWS SQS	Managed queue	AWS-native, simple task queue, serverless	Very high (managed)	Up to 14 days
AWS SNS	Pub/sub notification	Fan-out to many subscribers (email, SMS, Lambda, SQS)	Very high (managed)	No retention
Google Pub/Sub	Managed streaming	GCP-native, global, serverless	Very high (managed)	Up to 7 days
Redis Pub/Sub	In-memory pub/sub	Real-time notifications, low latency, fire-and-forget	Very high	None (no retention)
NATS	Lightweight messaging	IoT, microservices, low latency	Very high	JetStream adds retention

Decision Matrix

Need event replay / audit trail?
  YES → Kafka or Kinesis

Need simple task queue with retries and DLQ?
  AWS shop → SQS
  Self-hosted → RabbitMQ

Need real-time pub/sub with no persistence?
  Redis Pub/Sub or NATS

Need fan-out to multiple consumers?
  Kafka (consumer groups) or SNS → SQS fan-out

Need < 5 minutes