Books & Resources (with Learning Outcomes)

Database Theory & Design

Curated books with layered learning outcomes across foundations, modeling, systems internals, distributed data, warehousing, streaming, performance, and search.

Foundations

Database System Concepts
Abraham Silberschatz, Henry F. Korth, S. Sudarshan
  • Model data with ER and convert to normalized schemas.
  • Write correct SQL across DDL/DML and constraints.
  • Understand concurrency control, transactions, recovery.
Fundamentals of Database Systems
Ramez Elmasri, Shamkant Navathe
  • Master conceptual design and relational mapping.
  • Apply BCNF / 4NF decomposition and dependency analysis.
  • Compare logical vs physical design trade‑offs.
Database Management Systems
Raghu Ramakrishnan, Johannes Gehrke
  • Explain storage, buffer managers, and B+-trees.
  • Trace cost-based query optimization & join ordering.
  • Build intuition for transactions and logging.

Modeling & Design

Database Design for Mere Mortals
Michael J. Hernandez
  • Elicit requirements & translate to tables and keys.
  • Avoid common schema anti‑patterns.
  • Document business rules in the data model.
Data and Reality
William Kent
  • Recognize modeling ambiguities & semantic pitfalls.
  • Differentiate identifiers, categories, relationships.
  • Design schemas that reflect real‑world meaning.

Practitioner Overview

Designing Data‑Intensive Applications
Martin Kleppmann
  • Map end‑to‑end flows across OLTP / OLAP / streaming.
  • Compare consensus, replication, partitioning strategies.
  • Select storage engines & indexes by workload.

Systems & Internals

Database Systems: The Complete Book
Garcia-Molina, Ullman, Widom
  • Bridge relational theory with system implementation.
  • Understand cost models & physical operators.
  • Survey data warehousing, IR, recursion topics.
Transaction Processing
Jim Gray, Andreas Reuter
  • Analyze ACID properties & correctness criteria.
  • Compare 2PL, OCC, timestamp ordering.
  • Design recovery with logging & checkpoints.
Database Internals
Alex Petrov
  • Understand pages, WAL, compaction processes.
  • Contrast B‑tree and LSM trade‑offs.
  • Tune write/read amplification & space usage.

Distributed & NoSQL

Principles of Distributed Database Systems
Özsu, Valduriez
  • Reason about partitioning & replication strategies.
  • Evaluate distributed query processing & optimization.
  • Understand CAP, consistency levels, protocols.
NoSQL Distilled
Pramod Sadalage, Martin Fowler
  • Choose between document, key-value, column, graph.
  • Match workloads to consistency / availability tradeoffs.
  • Adopt polyglot persistence patterns.
Seven Databases in Seven Weeks
Perkins, Redmond, Wilson
  • Gain practical exposure to varied data models.
  • Evaluate operational vs analytical strengths.
  • Make informed trade‑offs for new projects.

Analytics & Warehousing

The Data Warehouse Toolkit
Ralph Kimball, Margy Ross
  • Design star / snowflake schemas for BI.
  • Model slowly changing dimensions & facts.
  • Plan data staging & ETL patterns.

Streaming & Real‑time

Streaming Systems
Tyler Akidau, Slava Chernyak, Reuven Lax
  • Model unbounded data w/ event‑time semantics.
  • Apply windowing, triggers, watermarking.
  • Design reliable real‑time pipelines.

Performance & Tuning

SQL Performance Explained
Markus Winand
  • Interpret execution plans & cardinality estimates.
  • Design effective indexes for workloads.
  • Refactor SQL for cost-based optimizers.
High Performance MySQL
Schwartz, Zaitsev, Tkachenko et al.
  • Tune InnoDB and query performance.
  • Operate replication & sharding at scale.
  • Resolve production bottlenecks methodically.

Search & Vectors

Introduction to Information Retrieval
Manning, Raghavan, Schütze
  • Understand indexing, retrieval models, ranking.
  • Build blocks for hybrid keyword + vector search.
  • Ground vector databases in classical IR.