databases
Practical resources about databases for software engineers.
89 results
Storing, Querying, and Scaling Data
Databases are the persistence layer every application depends on. Choosing between relational and NoSQL, designing indexes, handling migrations, and optimizing slow queries are skills that directly impact user experience and infrastructure cost.
This section covers recipes for PostgreSQL and MySQL connections, MongoDB CRUD operations, Redis caching strategies, and schema design patterns. You will also find guides on ACID transactions, connection pooling, and full-text search implementation.
Database Indexing Strategies — From B-Trees to BRIN
A practical guide to database indexes: B-Trees, Hash, GIN, GiST, BRIN, and partial indexes. Learn...
NoSQL Database Selection — MongoDB, DynamoDB, Cassandra
A practical guide to choosing the right NoSQL database. Compare document, key-value, wide-column,...
NoSQL Data Modeling Patterns
A practical guide to NoSQL data modeling: embedding vs referencing, access pattern-driven design,...
SQL CTEs: Common Table Expressions Explained
A practical guide to SQL CTEs: non-recursive and recursive expressions, readability, performance,...
SQL Joins — Visual Guide with Examples
A visual guide to SQL joins: INNER, LEFT, RIGHT, FULL OUTER, CROSS, and SELF joins with practical...
SQL Window Functions — Complete Guide
A practical guide to SQL window functions: ROW_NUMBER, RANK, DENSE_RANK, LEAD, LAG, SUM, AVG over...
Time-Series Databases — InfluxDB, TimescaleDB, ClickHouse
Practical guide to time-series databases: when to use a TSDB, data model, retention policies, and...
Vector Databases in Practice: Embeddings & Similarity Search
Build your first vector search pipeline: embeddings, ANN indexes, similarity search with pgvector...
Complete Guide to Serverless Databases
Choose and operate serverless databases for event-driven apps: DynamoDB, Aurora Serverless,...
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