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Databases & Vector DBs

Specialization domain#18 of 20 by depth

Database Technologies

Behind every app, website and dashboard sits a database quietly doing the real work, and this domain teaches you to build and run that layer well. You will learn the leading relational, document and vector databases companies depend on for speed and reliability at scale. Courses cover schema design, performance tuning, replication and the newer databases built specifically for AI-driven search. You come away able to keep data fast, safe and easy for everyone else on the team to build on.

Oracle 23ai
MongoDB
Redis
Neo4j
Pinecone
Vector DBs

47+Courses in this domain

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Domain Scope

Where Databases & Vector DBs fits in real work today

This domain covers the storage layer everything else is built on: how data is modelled, indexed and queried, how it stays consistent under load, and how it survives hardware and human failure.

It runs from relational fundamentals through document, key-value and graph stores, and now into the vector databases that AI-driven search and retrieval systems depend on.

47+

Courses in this domain

#18

Of 20 by catalogue depth

Career tracks mapped

Core technologies covered

Depth against nearby domains

This domain and its closest neighbours out of 20, ranked by how many courses each catalogue carries. Longer bar means a deeper catalogue.

IAM & Zero Trust#17 · 66
Databases & Vector DBs#18 · 47
Real Estate#19 · 47
API & Integration#20 · 36

Databases & Vector DBs holds 1% of the 20-domain catalogue.

How hands-on each technology gets

An editorial reading of how much of the work is keyboard-on time rather than concepts. Not a course count.

Oracle 23ai75
MongoDB65
Redis50
Neo4j60
Pinecone55
Vector & Embedding Stores70

Higher means more lab, build and troubleshooting work; lower means more concept, policy and design work.

Career Tracks

8 routes through this domain

Ordered foundational to specialised. Bar length is how much weight the track carries inside the domain — most learners complete one or two of these, not all eight.

Relational Database FundamentalsBeginner · 4–5 wks
SQL Query Craft & OptimisationBeginner · 3–5 wks
Oracle AdministrationIntermediate · 6–8 wks
NoSQL & Document StoresIntermediate · 4–6 wks
Caching & In-Memory DataIntermediate · 3–4 wks
Graph DatabasesAdvanced · 4–6 wks
Vector Databases for AIAdvanced · 3–5 wks
High Availability & RecoveryAdvanced · 5–7 wks

BeginnerIntermediateAdvancedDurations are typical study time, not a fixed schedule.

The path most learners take

Three steps in sequence, then one specialisation. Picking a single branch is normal — finishing all four is not the expectation.

Step 1
Relational Database Fundamentals
Step 2
SQL Query Craft & Optimisation
Step 3
A Primary Database Platform

Then one of

Oracle AdminNoSQL StoresVector & AI SearchHA & Recovery

Before you start

What to have ready before the foundations track. Everything else is taught from scratch.

Can write a basic SELECT statement
Understand tables, rows and keys
Command-line comfort helps
No administration experience needed to start

Technology Reference

What you actually learn, tool by tool

TechnologyHands-on depthWhat you work on

Oracle 23ai75Instance architecture, tuning, RAC concepts, backup and recovery with RMAN
MongoDB65Document modelling, aggregation pipelines, indexing and replica sets
Redis50Caching patterns, data structures, persistence trade-offs and pub/sub
Neo4j60Property graphs, Cypher queries and modelling relationship-heavy data
Pinecone55Vector indexes, similarity search, metadata filtering and hybrid retrieval
Vector & Embedding Stores70Embedding choice, chunking, recall tuning and pgvector alternatives

The full technology list for this domain is Oracle 23ai, MongoDB, Redis, Neo4j, Pinecone & Vector DBs — the six above are the ones the catalogue goes deepest on.

Why This Domain, Right Now