NoSQL database types (document, key-value, column, graph) in DBMS Theory - Step-by-Step Execution

Concept Flow - NoSQL database types (document, key-value, column, graph)

Start: Choose NoSQL type

↓

Use case decides best fit

You pick a NoSQL type based on data structure: documents, key-value pairs, columns, or graphs.

Execution Sample

DBMS Theory

INSERT INTO DocumentDB {"name": "Alice", "age": 30}
PUT KeyValueDB "user123" "Alice"
INSERT INTO ColumnDB (user_id, name) VALUES (123, "Alice")
CREATE NODE GraphDB (id:1, name:"Alice")
CREATE EDGE GraphDB (from:1, to:2, relation:"friend")

Shows how data is stored differently in each NoSQL type.

Analysis Table

Step	Database Type	Operation	Data Stored	Internal Structure	Result
1	Document	Insert	{"name": "Alice", "age": 30}	JSON-like document	Document stored with fields name and age
2	Key-Value	Put	Key: "user123", Value: "Alice"	Simple key-value pair	Key-value pair stored
3	Column	Insert	user_id=123, name="Alice"	Columns grouped in families	Row inserted with columns
4	Graph	Create Node	Node id=1, name="Alice"	Node with properties	Node created
5	Graph	Create Edge	Edge from node 1 to 2, relation="friend"	Edge connecting nodes	Edge created linking nodes
6	-	-	-	-	Execution ends after all inserts

💡 All data inserted into respective NoSQL database types

State Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	After Step 4	After Step 5	Final
DocumentDB	empty	{"name": "Alice", "age": 30}	{"name": "Alice", "age": 30}	{"name": "Alice", "age": 30}	{"name": "Alice", "age": 30}	{"name": "Alice", "age": 30}	{"name": "Alice", "age": 30}
KeyValueDB	empty	empty	{"user123": "Alice"}	{"user123": "Alice"}	{"user123": "Alice"}	{"user123": "Alice"}	{"user123": "Alice"}
ColumnDB	empty	empty	empty	Row with user_id=123, name="Alice"	Row with user_id=123, name="Alice"	Row with user_id=123, name="Alice"	Row with user_id=123, name="Alice"
GraphDB Nodes	empty	empty	empty	Node 1: {name: "Alice"}	Node 1: {name: "Alice"}	Node 1: {name: "Alice"}	Node 1: {name: "Alice"}
GraphDB Edges	empty	empty	empty	empty	empty	Edge from 1 to 2: {relation: "friend"}	Edge from 1 to 2: {relation: "friend"}

Key Insights - 3 Insights

Why does the Document database store data as JSON-like documents instead of simple key-value pairs?

Because Document databases store complex, nested data with multiple fields in one document, unlike Key-Value databases which store only simple pairs. See execution_table rows 1 and 2.

How is data organized differently in Column databases compared to Document databases?

Column databases group data by columns in families for fast queries on specific columns, while Document databases store whole documents. See execution_table rows 1 and 3.

Why do Graph databases have nodes and edges instead of just storing data like other NoSQL types?

Graph databases model relationships explicitly with edges connecting nodes, which helps with connected data queries. See execution_table rows 4 and 5.

Visual Quiz - 3 Questions

Look at the execution_table at step 2. What kind of data is stored in the Key-Value database?

A A simple key and its associated value

B A JSON document with multiple fields

C Columns grouped in families

D Nodes and edges representing relationships

💡 Hint

Check the 'Data Stored' column at step 2 in execution_table

At which step does the Graph database create a connection between two nodes?

A Step 3

B Step 5

C Step 4

D Step 1

💡 Hint

Look for 'Create Edge' operation in execution_table

If you want to store user profiles with many fields and nested data, which NoSQL type from the table is best?

A Key-Value database

B Column database

C Document database

D Graph database

💡 Hint

See execution_table row 1 for storing complex data

Concept Snapshot

NoSQL databases store data differently:
- Document: JSON-like documents with fields
- Key-Value: simple key and value pairs
- Column: data in columns grouped by families
- Graph: nodes connected by edges
Choose type based on data shape and query needs.

Full Transcript

NoSQL databases come in four main types: document, key-value, column, and graph. Document databases store data as JSON-like documents with multiple fields, good for complex data. Key-value databases store simple pairs of keys and values, ideal for fast lookups. Column databases organize data by columns grouped in families, useful for queries on specific columns. Graph databases store nodes and edges to represent connected data and relationships. Each type suits different use cases depending on data structure and query patterns.