SQL vs. NoSQL

Common types of NoSQL

Key-value stores

Array of key-value pairs. The "key" is an attribute name.
Redis, Vodemort, Dynamo.

Document databases

Data is stored in documents.
Documents are grouped in collections.
Each document can have an entirely different structure.
CouchDB, MongoDB.

Wide-column / columnar databases

Column families - containers for rows.
No need to know all the columns up front.
Each row can have different number of columns.
Cassandra, HBase.

Graph database

Data is stored in graph structures
- Nodes: entities
- Properties: information about the entities
- Lines: connections between the entities
Neo4J, InfiniteGraph

Differences between SQL and NoSQL

Storage

SQL: store data in tables.
NoSQL: have different data storage models.

Schema

SQL
- Each record conforms to a fixed schema.
- Schema can be altered, but it requires modifying the whole database.
NoSQL:
- Schemas are dynamic.

Querying

SQL
- Use SQL (structured query language) for defining and manipulating the data.
NoSQL
- Queries are focused on a collection of documents.
- UnQL (unstructured query language).
- Different databases have different syntax.

Scalability

SQL
- Vertically scalable (by increasing the horsepower: memory, CPU, etc) and expensive.
- Horizontally scalable (across multiple servers); but it can be challenging and time-consuming.
NoSQL
- Horizontally scalable (by adding more servers) and cheap.

ACID

Atomicity, consistency, isolation, durability
SQL
- ACID compliant
- Data reliability
- Guarantee of transactions
NoSQL
- Most sacrifice ACID compliance for performance and scalability.

Which one to use?

SQL

Ensure ACID compliance.
- Reduce anomalies.
- Protect database integrity.
Data is structured and unchanging.

NoSQL

Data has little or no structure.
Make the most of cloud computing and storage.
- Cloud-based storage requires data to be easily spread across multiple servers to scale up.
Rapid development.
- Frequent updates to the data structure.