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References: Databases and SQL

  1. Relational Database - Wikipedia Explains the relational model, including tables, rows, columns, and how data relationships are maintained through keys. Foundational knowledge for PMs who need to understand how application data is structured and queried.

  2. SQL (Structured Query Language) - Wikipedia Covers the history, syntax, and capabilities of SQL as the standard language for relational database management. Essential background for PMs who encounter queries in data analysis, reporting, or engineering discussions.

  3. NoSQL Database - Wikipedia Describes NoSQL database categories including document stores, key-value stores, and graph databases with trade-off analysis. Helps PMs understand when teams choose NoSQL over relational databases for specific use cases.

  4. Beaulieu, Alan. Learning SQL. 3rd Edition, O'Reilly Media, 2020. Hands-on introduction to SQL covering queries, joins, subqueries, and data manipulation with practical exercises. Gives PMs enough SQL literacy to write basic queries and understand data models independently.

  5. Kleppmann, Martin. Designing Data-Intensive Applications. O'Reilly Media, 2017. Deep exploration of database internals, data modeling, replication, and distributed storage system trade-offs. Provides PMs with the conceptual framework to evaluate data architecture decisions and their product implications.

  6. SQL Tutorial - W3Schools Interactive SQL tutorial covering SELECT statements, JOINs, filtering, and aggregation with hands-on practice. An accessible starting point for PMs who want to learn enough SQL to query databases themselves.

  7. Database Normalization Explained - Guru99 Step-by-step explanation of normalization forms (1NF through 3NF) with examples showing how they reduce data redundancy. Helps PMs understand why database schema design matters for data integrity and application performance.

  8. Primary and Foreign Keys - PostgreSQL Documentation Official PostgreSQL documentation explaining key constraints, referential integrity, and how tables relate to each other. Gives PMs precise understanding of how data relationships are enforced at the database level.

  9. SQL vs NoSQL Databases - MongoDB MongoDB's comparison of relational and non-relational databases covering data models, scalability, and flexibility trade-offs. Useful for PMs evaluating database technology choices alongside their engineering teams.

  10. Introduction to Document Databases - Couchbase Explains how document databases store data as flexible JSON-like documents rather than rigid table schemas. Relevant for PMs working with products that use document stores for content management or user profiles.