Databases is the foundational layer underneath every persistent application. The category here covers the breadth of modern database technology rather than any single product: relational databases (PostgreSQL, MySQL, SQL Server), document stores (MongoDB, Couchbase), key-value stores (Redis, DynamoDB), column-oriented warehouses (BigQuery, Snowflake, ClickHouse), time-series databases (TimescaleDB, InfluxDB), and graph databases (Neo4j).
Choosing a database is rarely about one being faster than another in benchmarks. It's about access patterns: how data is read and written, how strict your consistency needs are, how big the data set will grow, and what kind of queries dominate. Picking PostgreSQL for everything is a defensible default; picking the wrong NoSQL store for the wrong workload is one of the most expensive mistakes a startup can make.
What you'll work with in these 25 courses
- Relational fundamentals: ACID, normalization, indexes, query plans
- PostgreSQL deep dives: extensions, JSONB, partitioning, replication
- MongoDB and document modeling: schema design, aggregation pipeline
- Caching and key-value: Redis data structures, Memcached
- Analytical databases: ClickHouse, DuckDB, BigQuery, Snowflake
- Operational concerns: backups, point-in-time recovery, sharding, failover