Advanced level · Module 5: NoSQL and Choosing a Data Store · Lesson 1 of 4
The NoSQL Landscape
Learn the main non-relational models and what each is good at.
In this lesson you will
- Describe document, key-value, wide-column and graph databases
- Explain the trade-offs compared with relational databases
Key concepts
document databasekey-value storewide-column and graphschema flexibility
The lesson
Document databases such as MongoDB store records as JSON-like documents that can vary in shape. Key-value stores such as Redis keep simple values by key in memory, which makes them extremely fast for caching and sessions.
Wide-column stores handle very large, write-heavy data spread across many servers, and graph databases model relationships such as networks of people or referrals.
These systems trade some features of relational databases — joins, constraints, strict schemas, sometimes strong consistency — for flexibility or scale. Most organisations' core records still fit relational databases best.
Step by step
- Match five example workloads to suitable database types.
- Store and read values in a key-value store.
- Insert documents of different shapes into a document database.
- List what you lose compared with PostgreSQL.
Practice activity
Write a one-page comparison of four database types with an example use for each.
Expected result: An accurate comparison with realistic examples and trade-offs.
Check your understanding
-
What is a key-value store well suited to?
Show answer
Very fast lookups such as caching and sessions.
-
What do many NoSQL databases give up compared with relational ones?
Show answer
For example joins, constraints or strict schemas.
Taught live by an instructor — online or in person. Free course lessons are for self-study and do not lead to a certificate — see registration options.