283 lines
7.1 KiB
Markdown
283 lines
7.1 KiB
Markdown
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# Introduction
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ZipponDB is a relational database written entirely in Zig from stractch with 0 dependency.
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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.
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### Why Zippon ?
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- Open-source and written 100% in Zig with 0 dependency
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- Relational database
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- Simple and minimal query language
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- Small, light, fast and implementable everywhere
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# Declare a schema
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ZipponDB need a schema to work. A schema is a way to define how your data will be store.
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Compared to SQL, you can see it as a file where you declare all table name, columns name, data type and relationship.
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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:
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```
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User (
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name: str,
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email: str,
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best_friend: User,
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)
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```
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Note that the best friend is a link to another User.
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Here a more advance example with multiple struct:
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```
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User {
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name: str,
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email: str,
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friends: []User,
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posts: []Post,
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liked_posts: []Post,
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comments: []Comment,
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liked_coms: []Comment,
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}
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Post {
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title: str,
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image: str,
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at: date,
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from: User,
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like_by: []User,
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comments: []Comment,
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}
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Comment {
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content: str,
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at: date,
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from: User,
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like_by: []User,
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of: Post,
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}
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```
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Can be simplify to take less space but can require more complexe query:
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```
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User {
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name: str,
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email: str,
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friends: []User,
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posts: []Post,
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comments: []Comment,
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}
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Post {
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title: str,
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image: str,
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at: date,
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like_by: []User,
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comments: []Comment,
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}
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Comment {
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content: str,
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at: date,
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like_by: []User,
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}
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```
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Note: [] are list of value.
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# ZipponQL
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ZipponDB use it's own query language, ZipponQL or ZiQL for short. Here the keys point to remember:
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- 4 actions available: `GRAB` `ADD` `UPDATE` `DELETE`
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- All query start with an action then a struct name
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- {} Are filters
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- [] Are how much; what data
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- () Are new or updated data (Not already in file)
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- || Are additional options
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- By default all member that are not link are return
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- To return link or just some member, specify them between []
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## GRAB
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The main action is `GRAB`, this will parse files and return data. Here how it's work:
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```
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GRAB StructName [number_of_entity_max; member_name1, member_name2] { member_name1 = value1}
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```
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Note that `[]` and `{}` are both optional.
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So this will work and return all User without any filtering:
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```
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GRAB User
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```
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Here a simple example where to get all User above 18 years old:
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```
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GRAB User {age > 18}
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```
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To just return the name of User:
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```
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GRAB User [name] {age > 18}
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```
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To return the 10 first User:
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```
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GRAB User [10] {age > 18}
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```
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You can use both:
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```
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GRAB User [10; name] {age > 18}
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```
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To order it using the name:
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```
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GRAB User [10; name] {age > 10} |ASC name|
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```
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## ADD
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The `ADD` action will add one entity into the database (batch are comming).
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The synthax is similare but use `()`, this mean that the data is not yet in the database if between `()`.
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Here an example:
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```
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ADD User (name = 'Bob', age = 30, email = 'bob@email.com', scores = [1 100 44 82])
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```
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You need to specify all member when adding an entity (default value are comming).
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## DELETE
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Similare to `GRAB` but delete all entity found using the filter and return the list of UUID deleted.
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```
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DELETE User {name = 'Bob'}
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```
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## UPDATE
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A mix of `GRAB` and `ADD`. This take a filter first, then the new data.
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Here we update the 5 first User named `adrien` to add a capital and become `Adrien`.
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```
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UPDATE User [5] {name='adrien'} => (name = 'Adrien')
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```
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Note that compared to `ADD`, you don't need to specify all member between `()`. Only the one specify will be updated.
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## Examples list
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| Command | Description |
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| --- | --- |
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| GRAB User | Get all users |
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| GRAB User { name = 'Adrien' } | Get all users named Adrien |
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| GRAB User [1; email] | Get one user's email |
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| GRAB User \| ASC name \| | Get all users ordered by name |
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| GRAB User [name] { age > 10 AND name != 'Adrien' } | Get users' name if more than 10 years old and not named Adrien |
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| GRAB User { age > 10 AND (name = 'Adrien' OR name = 'Bob'} | Use multiple condition |
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| UPDATE User [1] { name = 'Adrien' } => ( email = 'new@email.com' ) | Update a user's email |
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| REMOVE User { id = '000-000' } | Remove a user by ID |
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| ADD User ( name = 'Adrien', email = 'email', age = 40 ) | Add a new user |
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### Not yet implemented
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| Command | Description |
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| --- | --- |
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| GRAB User { age > 10 AND name IN ['Adrien' 'Bob']} | In comparison |
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| GRAB User [1] { bestfriend IN { name = 'Adrien' } } | Get one user that has a best friend named Adrien |
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| GRAB User [10; friends [1]] { age > 10 } | Get one friend of the 10th user above 10 years old |
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| GRAB Message [100; comments [ date ] ] { writter IN { name = 'Adrien' }.bestfriend } | Get the date of 100 comments written by the best friend of a user named Adrien |
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| GRAB User { IN Message { date > '12-01-2014' }.writter } | Get all users that sent a message after the 12th January 2014 |
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| GRAB User { !IN Comment { }.writter } | Get all users that didn't write a comment |
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| GRAB User { IN User { name = 'Adrien' }.friends } | Get all users that are friends with an Adrien |
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# Data types
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Their is 5 data type for the moment:
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- `int`: 64 bit integer
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- `float`: 64 bit float
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- `bool`: Boolean, can be `true` or `false`
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- `string`: Character array between `''`
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- `uuid`: Id in the UUID format, used for relationship, ect. All struct have an id member.
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Comming soon:
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- `date`: A date in yyyy/mm/dd
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- `datetime`: A date time in yyyy/mm/dd/hh/mm/ss
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- `time`: A time in hh/mm/ss
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All data type can be an array of those type using [] in front of it. So []int is an array of integer.
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All data type can also be `null`. Expect array that can only be empty.
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# Lexique
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- **Struct:** A struct of how to store data. E.g. `User`
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- **Entity:** An entity is one instance of a struct.
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- **Member:** A member is one data saved in a struct. E.g. `name` in `User`
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# How does it work ?
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TODO: Create a tech doc of what is happening inside.
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# Roadmap
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#### v0.1 - Base
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- [X] UUID
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- [X] CLI
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- [X] Tokenizers
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- [ ] ZiQL parser
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- [ ] Schema engine
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- [X] File engine
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- [ ] Loging
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#### v0.2 - Usable
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- [ ] B-Tree
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- [ ] Relationships
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- [ ] Date
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- [ ] Docker
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#### v0.3 - QoL
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- [ ] Schema migration
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- [ ] Dump/Bump data
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- [ ] Recovery
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- [ ] Better CLI
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#### v0.4 - Usability
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- [ ] Server
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- [ ] Python interface
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- [ ] Go interface
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#### v0.5 - In memory
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- [ ] In memory option
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- [ ] Cache
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#### v0.6 - Performance
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- [ ] Transaction
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- [ ] Multi threading
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- [ ] Lock manager
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#### v0.7 - Safety
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- [ ] Auth
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- [ ] Metrics
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- [ ] Durability
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#### v0.8 - Advanced
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- [ ] Query optimizer
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#### v0.9 - Docs
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- [ ] ZiQL tuto
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- [ ] Deployment tuto
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- [ ] Code docs
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- [ ] CLI help
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#### v1.0 - Web interface
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- [ ] Query builder
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- [ ] Tables
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- [ ] Schema visualization
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- [ ] Dashboard metrics
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Let's see where it (or my brain) start explode ;)
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