Introduction to databases and persistence

Teachers

What is a Database?

At its simplest, a Database is an organized collection of data. It is usually stored electronically on a computer system.

Analogy: If you use JavaScript, think of a variable holding an Array or an Object. This is a tiny, temporary database. It holds data for you to use while your program runs.
Analogy: A spreadsheet (like Excel) is a manual database. It has rows and columns. You can sort, filter, and calculate values.
Analogy: A non-technical analogy would be going to the store after memorising the shopping list. The list has an order and as you go through it, in your head you are crossing items off it as you pick them up.

Databases can be simple, like a contact list on your phone. They can also be complex, like the systems powering Facebook or your bank.

The Concept of Persistence

Persistence means that data survives after the program finishes.

Analogy: Related to the above. While it is fun to memorise shopping lists as a way to train your memory, most people use a persistent version of the list i.e. they write it down on a piece of paper and cross items off the list as they pick them up. Even though the items on the list have left our head, we still have the list on the paper. The list persists beyond our attention span (mine is very short).

Without persistence, data only lives in your computer's RAM (temporary memory). If you turn off the computer or close the program, that data is lost.

Why do we need persistence?

Your notes had a great example about wolves marking territory or humans making cave paintings. Here is a technical summary:

**Durability:** Data must survive if the computer crashes or the power goes out.
History: We need to keep records of the past (like bank transactions).
Sharing: Many users need to look at the same data at different times.

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An aside: Humans are not the only ones that use persistence on purpose.

Wolves go around their territory peeing at key points to let other wolves know that they have claimed this area. Any other wolves that come along when the wolves are not there will be able to smell the scent and know someone else is already there.
Bears put a scratch mark on trees not only to show that this is their area, but also how big they are, the higher the mark the bigger the bear.

These are pretty basic uses of persistence, but it shows that persistence has been around for a long time 🙂

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Another aside:

Persistence existed before there was written language (but there was spoken language). The database was the lessons and rules of your tribe or cultural group, and the persistence layer were story tellers.

For centuries, information that was important to a group was told to everyone through stories by story tellers, who held a very important position in the group as the holder of the group’s wisdom. They would then have apprentices who would learn the stories and collected wisdom and tell it to the next generation. Eventually, these stories were written down.

We also see persistence in the form of drawings in the ancient cave paintings. They would communicate important information. And here we are thousands of years later and their information is still to be seen.

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In the physical world, we, now, use paper or books to persist information. For hundreds of years libraries were our databases, and books and magazines our way of keeping information safe for later use. In the digital world, we use Filesystems.

The Filesystem: The Foundation

Almost all databases store their data on a Filesystem (like the hard drive on your laptop).

The filesystem manages how data is written to the physical disk. A DBMS (Database Management System) is a specialized program. It manages these files efficiently for you.

Types of Database Systems

There is no "one size fits all" solution. Different problems need different databases.

Type	Description	Best For	Examples
Relational (RDBMS)	Data is stored in Tables with rows and columns. Relationships are strict. Uses SQL.	Financial systems, user accounts, inventory.	SQLite, PostgreSQL, MySQL
Document Store (NoSQL)	Data is stored as documents (similar to JSON). The structure is flexible.	Content management, fast prototyping.	MongoDB, CouchDB
Key-Value Store	Simple "dictionary" storage (Key -> Value). Very fast.	Caching (temporary storage), session management.	Redis, Memcached
Graph Database	Stores data as nodes (dots) and edges (lines). Great for connecting things.	Social networks, friend recommendations, navigation routing	Neo4j, Amazon Neptune
Search Engine	Optimized for searching text.	Search bars, analyzing logs.	Elasticsearch, Solr
Time Series	Optimized for measuring change over time.	Sensor data, stock market prices.	InfluxDB, Prometheus

Why focus on Relational Databases (SQL)?

Even with many new types of databases, Relational Databases are still the standard for most businesses.

Reliability: They guarantee that data won't be lost or corrupted.
Structure: They force you to organize your data. This reduces bugs in the future.
Flexibility: SQL allows you to ask complex questions (Queries about your data. You don't need to write complex code to loop through files yourself.

Key Terms Summary

Term	Definition
Database	An organized collection of information.
DBMS	Database Management System. The software that manages the database (e.g., PostgreSQL).
Server	A program that runs in the background and listens for requests.
Client	The program that connects to the server (e.g., your Node.js app).
Query	A request for data from a database.

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