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Database Knowledge Transfer - Complete Guide

Welcome to the comprehensive database engineering guide! This folder contains everything you need to know about databases from basics to advanced scaling concepts.

Guide Structure

Fundamentals
  1. 01 - Introduction to Databases - What databases are, types, architecture basics
  2. 02 - Relational Databases & SQL - SQL deep dive, queries, stored procedures
  3. 03 - Database Design & Normalization - Schema design, ER diagrams, normalization forms
  4. 04 - Indexing Deep Dive - B-trees, index types, query optimization with indexes
  5. 05 - Transactions & ACID - ACID properties, isolation levels, locking
Scaling & NoSQL
programming-language-concepts.md
zero-language-explanation.md
DB
01-introduction.md
02-relational-databases.md
03-database-design.md
04-indexing.md
05-transactions-acid.md
06-nosql-databases.md
07-query-optimization.md
08-replication-ha.md
09-sharding-partitioning.md
10-caching-strategies.md
11-cap-theorem.md
12-connection-pooling.md
13-backup-recovery.md
14-monitoring.md
15-database-selection.md
README.md
JS
Event loop
Merlin Backend
01-Orchestration.md
02-DeepResearch.md
03-Search.md
04-Scraping.md
05-Streaming.md
06-MultiProviderLLM.md
07-MemoryAndContext.md
08-ErrorHandling.md
09-RateLimiting.md
10-TaskQueue.md
11-SecurityAndAuth.md
Orchestration-2nd-draft
OpenAI Agents Python
00_OVERVIEW.md
01_AGENT_SYSTEM.md
02_RUNNER_SYSTEM.md
03_TOOL_SYSTEM.md
04_ITEMS_SYSTEM.md
05_GUARDRAILS.md
06_HANDOFFS.md
07_MEMORY_SESSIONS.md
08_MODEL_PROVIDERS.md
09_SANDBOX_SYSTEM.md
10_TRACING.md
11_RUN_STATE.md
12_CONTEXT.md
13_LIFECYCLE_HOOKS.md
14_CONFIGURATION.md
15_ERROR_HANDLING.md
16_STREAMING.md
17_EXTENSIONS.md
18_MCP_INTEGRATION.md
19_BEST_PRACTICES.md
20_ARCHITECTURE_PATTERNS.md
opencode-study
context-handling
core
Python
Alembic
Basics
sqlalchemy - fastapi
SQLAlchemy overview
tweets
system_design_for_agentic_apps.md
  1. 06 - NoSQL Databases - Document, key-value, wide-column, graph, time-series
  2. 07 - Query Optimization - EXPLAIN, execution plans, optimization techniques
  3. 08 - Replication & High Availability - Primary-replica, failover, CAP tradeoffs
  4. 09 - Sharding & Partitioning - Horizontal scaling, data distribution
  5. 10 - Caching Strategies - Cache patterns, Redis, cache invalidation
Distributed Systems & Operations
  1. 11 - CAP Theorem & Distributed Systems - CAP theorem, consistency models, consensus
  2. 12 - Connection Pooling & Performance - Pool architecture, sizing, best practices
  3. 13 - Backup & Recovery - Backup types, PITR, disaster recovery
  4. 14 - Monitoring & Observability - Metrics, logging, alerting, dashboards
  5. 15 - Choosing the Right Database - Decision framework, database comparison

How to Use This Guide

For Beginners

Start with files 01-05 to build a solid foundation in relational databases. Practice SQL examples and understand normalization.

For Intermediate Engineers

Focus on files 04-10 covering performance, scaling, and NoSQL options. These are crucial for real-world applications.

For Senior/Staff Engineers

Deep dive into files 11-15 covering distributed systems theory, operations, and decision-making frameworks.

Quick Reference

Database Types Quick Pick
Use CaseRecommended Database
General application dataPostgreSQL
Cache/sessionsRedis
SearchElasticsearch
Time-series metricsTimescaleDB/InfluxDB
Global scale writesCassandra
Graph relationshipsNeo4j
Document storeMongoDB
Performance Checklist
  • Proper indexes on query columns
  • Connection pooling configured
  • Query execution plans reviewed
  • Caching layer implemented
  • Replication for read scaling
  • Partitioning for large tables
  • Monitoring in place
Scaling Path
  1. Optimize queries and indexes
  2. Add read replicas
  3. Implement caching
  4. Partition large tables
  5. Shard if necessary
  6. Consider specialized databases

Additional Resources

Books
  • "Designing Data-Intensive Applications" by Martin Kleppmann (The Bible)
  • "PostgreSQL: Up and Running"
  • "High Performance MySQL"
Online Resources
  • PostgreSQL Documentation (excellent)
  • Use The Index, Luke (indexing guide)
  • Database of Databases (dbdb.io)
Practice
  • Set up PostgreSQL locally and practice
  • Use EXPLAIN on your queries
  • Implement a caching layer
  • Configure read replicas
  • Simulate failures and practice recovery

Happy Learning! 🚀