ZipponDB goal is to be ACID, light, simple and high performance. It is aim for small to medium application that don't need fancy features but a simple and reliable database.

Why Zippon ?

Open-source and written 100% in Zig with 0 dependency
Relational database
Simple and minimal query language
Small, light, fast and implementable everywhere

Declare a schema

ZipponDB need a schema to work. A schema is a way to define how your data will be store.

Compared to SQL, you can see it as a file where you declare all table name, columns name, data type and relationship.

But here you declare struct. A struct have a name and members. A member is one data or link and have a type associated. Here a simple example for a user:

User (
    name: str,
    email: str,
    best_friend: User,
)

Note that the best friend is a link to another User.

Here a more advance example with multiple struct:

User {
    name: str,
    email: str,
    friends: []User,
    posts: []Post,
    liked_posts: []Post,
    comments: []Comment,
    liked_coms: []Comment,
}

Post {
    title: str,
    image: str,
    at: date,
    from: User,
    like_by: []User,
    comments: []Comment,
}

Comment {
    content: str,
    at: date,
    from: User,
    like_by: []User,
    of: Post,
}

Can be simplify to take less space but can require more complexe query:

User {
    name: str,
    email: str,
    friends: []User,
    posts: []Post,
    comments: []Comment,
}

Post {
    title: str,
    image: str,
    at: date,
    like_by: []User,
    comments: []Comment,
}

Comment {
    content: str,
    at: date,
    like_by: []User,
}

Note: [] are list of value.

ZipponQL

ZipponDB use it's own query language, ZipponQL or ZiQL. Here the keys point to remember:

{} Are filters
[] Are how much; what data
() Are new or updated data (Not already in file); Or to link condition between {}
|| Are additional options
By default all member that are not link are return
To return link or just some member, specify them between []

Examples

Command	Description
GRAB User	Get all users
GRAB User { name = 'Adrien' }	Get all users named Adrien
GRAB User [1; email]	Get one user's email
GRAB User \| ASC name \|	Get all users ordered by name
GRAB User [name] { age > 10 AND name != 'Adrien' }	Get users' name if more than 10 years old and not named Adrien
GRAB User { age > 10 AND (name = 'Adrien' OR name = 'Bob'}	Use multiple condition
UPDATE User [1] { name = 'Adrien' } => ( email = 'new@email.com' )	Update a user's email
REMOVE User { id = '000-000' }	Remove a user by ID
ADD User ( name = 'Adrien', email = 'email', age = 40 )	Add a new user

Not yet implemented

Command	Description
GRAB User { age > 10 AND name IN ['Adrien' 'Bob']}	Use multiple condition
GRAB User [1] { bestfriend = { name = 'Adrien' } }	Get one user that has a best friend named Adrien
GRAB User [10; friends [1]] { age > 10 }	Get one friend of the 10th user above 10 years old
GRAB Message [100; comments [ date ] ] { .writter = { name = 'Adrien' }.bestfriend }	Get the date of 100 comments written by the best friend of a user named Adrien
GRAB User { IN Message { date > '12-01-2014' }.writter }	Get all users that sent a message after the 12th January 2014
GRAB User { !IN Comment { }.writter }	Get all users that didn't write a comment
GRAB User { IN User { name = 'Adrien' }.friends }	Get all users that are friends with an Adrien

Lexique

Struct: A struct of how to store data. E.g. User
Entity: An entity is one instance of a struct.
Member: A member is one data saved in a struct. E.g. name in User

Roadmap

v0.1 - Base

UUID
CLI
Tokenizers
ZiQL parser
Schema management
File management
Loging

v0.2 - Usable

B-Tree
Relationships
Date
Docker

v0.3 - QoL

Schema migration
Dump/Bump data
Recovery
Better CLI

v0.4 - Usability

Server
Python interface
Go interface

v0.5 - In memory

In memory option
Cache

v0.6 - Performance

Transaction
Multi threading
Lock manager

v0.7 - Safety

Auth
Metrics
Durability

v0.8 - Advanced

Query optimizer

v0.9 - Docs

ZiQL tuto
Deployment tuto
Code docs
CLI help

v1.0 - Web interface

Query builder
Tables
Schema visualization
Dashboard metrics

Let's see where it (or my brain) start explode ;)