Data Access Layer
DAL is a proxy layer for SQL databases with a MongoDB inspired query interface. It can be used as a Go or NodeJS package (requires compiler). It is modular and allows to create your own proxy and apply custom middlewares.
Notes:
- This project is still in early alpha. You need to build it yourself and use at your own risk.
- At the time only SQLite is implemented, however, other drivers might work.
Use cases:
- For IOT networks when MySQL/PG are too heavy.
- If you need a layer between your application and the database (i.e. for caching).
- If you want a MongoDB-like query interface for your SQL db.
- When you need a SQLite proxy (useful to share datasets with services)
The most efficient way to use DAL is to run the server as a standalone service.
Build:
go build -o server
Run:
export SQLITE_DIRECTORY=/opt/data
./server
2024/08/21 22:01:54 Starting server on port 8118
2024/08/21 22:01:54 Using directory: /opt/data
Install:
pnpm add git+git@github.com:nesterow/dal.git
Method | Description | SQL |
---|---|---|
In(table: string) |
Select table | SELECT * FROM table |
Find(filter: object) |
Filter rows | SELECT * FROM table WHERE filter |
Fields(fields: string[]) |
Select fields | SELECT fields, FROM table |
Sort(sort) |
Sort rows | SELECT * FROM table ORDER BY sort |
Limit(limit: number) |
Limit rows | SELECT * FROM table LIMIT limit |
Offset(offset: number) |
Offset rows | SELECT * FROM table OFFSET offset |
Join({ $for: "t_2", $do: { "t.a": "b" } }) |
Join tables | SELECT * FROM table t JOIN t_2 ON t.a = b |
Insert({name: "J"}, {name: "B"}) |
Insert row | INSERT INTO table (name,) VALUES ('J', 'B') |
Set({name: "Julian"}) |
Update row (Find(filter).Set({})) | UPDATE table SET name = 'Julian' WHERE filter |
Delete() |
Delete row (Find(filter).Delete()) | DELETE FROM table WHERE filter |
As(DTO) |
Map rows to a DTO | SELECT * FROM table |
Rows() |
Get rows iterator | SELECT * FROM table |
Exec() |
Execute query (update, insert, delete) | SQL RESULT |
Query() |
Query database | DTO array |
Tx() |
Run in trasaction |
Filter | Description | SQL |
---|---|---|
{id: 1, num: 2} |
Equals, default filter | WHERE id = 1 AND num = 2 |
{id: { $eq: 1 }} |
Equals, explicit | WHERE id = 1 |
{id: { $gt: 1 }} |
Greater than | WHERE id > 1 |
{id: { $gte: 1 }} |
Greater than or equal | WHERE id >= 1 |
{id: { $lt: 1 }} |
Less than | WHERE id < 1 |
{id: { $lte: 1 }} |
Less than or equal | WHERE id <= 1 |
{id: { $ne: 1 }} |
Not equal | WHERE id != 1 |
{id: { $in: [1, 2] }} |
In | WHERE id IN (1, 2) |
{id: { $nin: [1, 2] }} |
Not in | WHERE id NOT IN (1, 2) |
{id: { $like: "a" }} |
Like | WHERE id LIKE '%a%' |
{id: { $nlike: "a" }} |
Not like | WHERE id NOT LIKE '%a%' |
{id: { $between: [1, 2] }} |
Between | WHERE id BETWEEN 1 AND 2 |
{id: { $nbetween: [1, 2] }} |
Not between | WHERE id NOT BETWEEN 1 AND 2 |
{id: { $glob: "\*son" }} |
Glob | WHERE id GLOB '*son' |
import { DAL } from "@nesterow/dal";
class UserDTO {
id: number = 0;
name: string = "";
data: string = "";
age: number | undefined;
}
const db = new DAL({
database: "test.sqlite",
url: "http://localhost:8111",
});
// SELECT * FROM test t WHERE name GLOB '*son' AND age >= 18
const rows = db
.In("test t")
.Find({
name: { $glob: "*son" },
age: { $gte: 18 },
})
.As(UserDTO) // Map every row to DTO
.Rows();
for await (const row of rows) {
console.log(row); // Jason, Jackson
}
The client uses a light builder and messagepack over http. It is relatively easy to implement a client in any language see the docs
While in alpha stage the project is free for research purposes. Later it will be released under MIT-like license with AI/dataset exclusion terms.