---
title: "Structured vs unstructured, NoSQL taxonomy"
subject: "Big Data Technologies"
chapter: 4
key: "semester_8/big_data_technologies:structured-unstructured-nosql-taxonomy"
source: https://www.bctengineer.com/q/semester_8/big_data_technologies/structured-unstructured-nosql-taxonomy
site: BCT Engineering
---

# Structured vs unstructured, NoSQL taxonomy

Big Data Technologies · Chapter 4: NoSQL

- Asked in: 2074 Bhadra, 8 marks
- Video: [Types of NoSQL Databases in Hindi ( Which one to use  and where ? )](https://www.youtube.com/watch?v=qxFj8X8n6CE) — Engineering Digest
- Answer checked by Claude Opus 5.5 (high effort) on 2026-10-14
- Page: https://www.bctengineer.com/q/semester_8/big_data_technologies/structured-unstructured-nosql-taxonomy
- Whole chapter: https://www.bctengineer.com/md/semester_8/big_data_technologies/chapter-4

## Question

Differentiate between structured and unstructured data and discuss the Taxonomy of NoSQL.

## Short answer

Structured data has a fixed schema (e.g., RDBMS tables), while unstructured data (e.g., text, images) lacks predefined format. NoSQL databases are categorized as key-value stores (Redis), document stores (MongoDB), column-family stores (HBase), and graph databases (Neo4j), each suited for different scalability and data model needs.

## Answer

#### Structured vs unstructured data

**Structured data** follows a fixed schema of rows and columns (e.g. a bank's customer table). **Unstructured data** has no predefined format or schema (e.g. text, images, video, emails, logs).

| Point | Structured | Unstructured |
|---|---|---|
| Schema | Predefined, fixed | None, free-form |
| Storage | RDBMS tables | Files, NoSQL, data lakes (HDFS) |
| Query | SQL | Search, text mining, MapReduce |
| Ease of analysis | Easy | Hard, needs processing |
| Share of all data | About 10 to 20% | About 80% |
| Examples | Student table, transactions | Photos, tweets, PDFs, video |

(Semi-structured data such as XML and JSON has tags but no rigid schema.)

#### Taxonomy of NoSQL

NoSQL ("Not Only SQL") databases are non-relational, schema-flexible, horizontally scalable stores. They are classified into four main types by data model.

1. **Key-Value stores:** data is a pair of unique key and an opaque value, accessed by key only. Very fast and simple; good for caching, sessions, shopping carts. Examples: Redis, Riak, DynamoDB, Memcached.
2. **Document stores:** data is stored as self-describing documents (JSON/BSON/XML) that can be nested and differ in structure. Supports querying on fields. Good for content management and catalogues. Examples: MongoDB, CouchDB.
3. **Column-family (wide-column) stores:** data is stored in rows with column families, and column values are stored together. Good for huge write volumes and analytics on large data. Examples: HBase, Cassandra, BigTable.
4. **Graph databases:** data is stored as nodes, edges and properties, optimised for traversing relationships. Good for social networks, recommendations and fraud detection. Examples: Neo4j, InfiniteGraph.

```text
            NoSQL
   +--------+--------+---------+
 Key-Value Document Column   Graph
 Redis    MongoDB  HBase    Neo4j
 Riak     CouchDB  Cassandra
```

The first three (key-value, document, column-family) are called **aggregate-oriented** databases, as they store a whole aggregate unit together, which suits clusters. Graph databases are relationship-oriented.

## Check yourself

The answer's key points as multiple-choice questions, with the correct option and why.

1. Which is an example of unstructured data?
   A. Bank customer table
   B. Student marks table
   C. Photos and videos
   D. Transaction table
   Answer: C. Unstructured data has no predefined schema, such as images, video, text and logs. (Key point: Structured data)

2. How is data accessed in a key-value store?
   A. By graph traversal
   B. By unique key only, with an opaque value
   C. By SQL joins
   D. By column family
   Answer: B. A key-value store maps a unique key to a value, which suits caches and sessions. (Key point: Key-value store)

3. Which NoSQL type stores nested self-describing JSON/BSON documents?
   A. Document store (MongoDB, CouchDB)
   B. Graph database
   C. Key-value store
   D. Column-family store
   Answer: A. Document stores keep flexible JSON/BSON documents and allow queries on fields. (Key point: Document store)

4. What are graph databases like Neo4j optimised for?
   A. Huge write volume
   B. Caching sessions
   C. Storing images
   D. Traversing relationships, e.g. social networks and fraud detection
   Answer: D. They store nodes, edges and properties, so relationship queries are efficient. (Key point: Graph databases)

## Related in Big Data Technologies

- [Column vs row-oriented NoSQL databases](https://www.bctengineer.com/question.md?key=semester_8%2Fbig_data_technologies%3Acolumn-oriented-nosql-row-oriented) — Big Data Technologies, chapter 4
- [NoSQL term and CAP theorem](https://www.bctengineer.com/question.md?key=semester_8%2Fbig_data_technologies%3Anosql-term-cap-theorem) — Big Data Technologies, chapter 4

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