Here is a solid, practical, and detailed roadmap that assumes you already know SQL at a working level, but want to rebuild from scratch and reach mastery (like an architect who can design complex, scalable, and high-performance database systems).
This roadmap is structured in 6 stages, with clear milestones, depth of coverage, and practice strategies.
Stage 1 – Absolute Foundations
Even though you know SQL, start fresh to re-wire fundamentals.
🔹 Core Topics
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What is a DBMS vs RDBMS
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Relational theory: tuples, relations, domains, keys
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SQL syntax basics (DDL, DML, DQL, DCL, TCL)
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Data types (numeric, text, date/time, JSON, enums, etc.)
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Basic queries:
SELECT,WHERE,ORDER BY,LIMIT,DISTINCT -
Basic filtering with
LIKE,BETWEEN,IN,IS NULL
🔹 Practice
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Build a sample Banking DB (accounts, customers, transactions).
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Write 20–30 queries daily → retrieval, filtering, simple reports.
Stage 2 – Core Querying & Joins
Here’s where you strengthen relational thinking.
🔹 Core Topics
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Primary/foreign keys, indexes, normalization up to 3NF
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INNER JOIN,LEFT JOIN,RIGHT JOIN,FULL JOIN,SELF JOIN -
Set operators:
UNION,INTERSECT,EXCEPT -
Aggregates:
COUNT,SUM,AVG,MIN,MAX -
GROUP BY+HAVING -
Subqueries: correlated vs uncorrelated
🔹 Practice
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Design an E-commerce DB (products, orders, payments, users).
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Write:
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“Top 10 customers by spending this month”
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“Find products never sold”
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“Revenue per product category”
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“Users who bought in Jan but not Feb”
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Stage 3 – Intermediate SQL & DB Design
Master modeling, integrity, and more advanced querying.
🔹 Core Topics
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Constraints:
CHECK,DEFAULT,UNIQUE,FOREIGN KEYwith cascade rules -
Indexing: B-tree, hash, covering indexes, composite indexes
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Views & materialized views
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Stored procedures, functions, triggers
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Window functions:
ROW_NUMBER,RANK,DENSE_RANK,NTILE -
Common Table Expressions (CTEs) and recursive queries
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Transactions & ACID properties
🔹 Practice
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Extend the e-commerce DB → add discounts, stock management, reviews.
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Write advanced analytics queries:
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“Top 3 products per category by sales” (window functions)
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“Customer purchase streaks” (recursive CTEs)
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“Inventory reorder alerts” (triggers)
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Stage 4 – Advanced SQL & Performance Tuning
Now you start thinking like an SQL performance engineer.
🔹 Core Topics
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Execution plans:
EXPLAIN, query optimizer -
Indexing strategies (covering, partial, filtered)
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Partitioning: range, list, hash, composite
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Denormalization trade-offs
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Sharding & replication concepts
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Locking & isolation levels (READ COMMITTED, REPEATABLE READ, SERIALIZABLE)
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Query rewriting for optimization
🔹 Practice
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Pick a 10M+ row dataset (e.g., public NYC taxi data).
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Run queries with/without indexes, measure performance.
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Experiment with partitioning for time-series data.
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Simulate deadlocks & practice avoiding them.
Stage 5 – Specialized SQL
Become versatile across SQL dialects & modern DB use-cases.
🔹 Core Topics
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Dialect differences: MySQL, PostgreSQL, SQL Server, Oracle
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JSON support in SQL (Postgres
jsonb, MySQLJSON_EXTRACT) -
Full-text search (
tsvector,MATCH() AGAINST) -
GIS / spatial queries (PostGIS, MySQL spatial extensions)
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Data warehousing concepts: star vs snowflake schemas
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OLTP vs OLAP workloads
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Analytical SQL in columnar DBs (Redshift, BigQuery, Snowflake)
🔹 Practice
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Use PostgreSQL + PostGIS → build queries like “Find customers within 5km of store X”.
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Try BigQuery/Snowflake → run analytical queries on billions of rows.
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Build a small data warehouse → ETL pipeline into fact & dimension tables.
Stage 6 – Database Architecture & Mastery
This is where you become a Database Architect.
🔹 Core Topics
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Designing databases for high concurrency & scaling
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Advanced normalization (BCNF, 4NF, 5NF) & when to denormalize
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Event sourcing & CQRS patterns
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Hybrid transactional/analytical systems (HTAP)
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Security: roles, privileges, row-level security, data masking
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Backup, replication, failover, clustering
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Cloud DBs: AWS RDS, Aurora, GCP CloudSQL, Azure SQL
🔹 Practice
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Design an end-to-end DB system for:
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Banking (real-time transactions, fraud detection)
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Social Media (feeds, likes, comments, search)
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Logistics (shipments, tracking, optimization)
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Review execution plans of real business queries weekly.
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Read Postgres/MySQL source code of query planner (deep dive).
