Polyglot Persistence

# Package: io.thecodeforge.python.system_design

# Typical polyglot architecture for an e-commerce system:

# PostgreSQL — relational: users, orders, products, payments
# - ACID transactions: order.create() and inventory.decrement() atomically
# - Complex queries: reporting, joins between entities
# - Example: user creates an order

# Redis — key-value: sessions, caching, rate limiting
# - Sub-millisecond reads: session token → user object
# - TTL-based expiry: sessions expire automatically
# - Example: cache product page for 10 minutes

# Elasticsearch — search: product search with relevance
# - Full-text search with typo tolerance
# - Faceted search: filter by price, brand, rating
# - Example: user searches 'wireless headphones'

# MongoDB (document) — product catalogue
# - Flexible schema: different products have different attributes
# - Laptop has CPU, RAM; T-shirt has size, colour
# - Example: store varied product attributes without schema migration

# Neo4j (graph) — social features, recommendations
# - 'Users who bought X also bought Y'
# - Friend-of-friend queries
# - Example: find all users within 3 hops in social graph

# InfluxDB (time-series) — metrics, analytics
# - Write-optimised for timestamped data
# - Example: page views, API response times

import asyncio

# When a product is created: must update PostgreSQL AND Elasticsearch
# Option 1: Dual write (naive — risks partial failure)
async def create_product_bad(product):
    await postgres.insert('products', product)      # succeeds
    await elasticsearch.index('products', product)  # what if this fails?
    # Product exists in Postgres but not in search — inconsistency

# Option 2: Write to primary, sync via CDC (Change Data Capture)
# Debezium reads PostgreSQL WAL → publishes to Kafka → Elasticsearch consumer
# Primary write is source of truth; Elasticsearch is eventually consistent

# Option 3: Outbox pattern
async def create_product_outbox(product):
    async with postgres.transaction():
        await postgres.insert('products', product)
        await postgres.insert('outbox', {
            'event': 'product_created',
            'data': product,
            'processed': False
        })
    # Separate process reads outbox and syncs to Elasticsearch
    # If it fails, retries safely (at-least-once delivery)

print('Outbox pattern ensures eventual consistency')