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https://github.com/elmarti/camadb
A NoSQL embedded database written in Typescript
https://github.com/elmarti/camadb
database electron embedded-database indexeddb nodejs nosql nosql-database typescript
Last synced: about 2 months ago
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A NoSQL embedded database written in Typescript
- Host: GitHub
- URL: https://github.com/elmarti/camadb
- Owner: elmarti
- License: mit
- Created: 2021-09-30T08:16:18.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2023-10-27T18:33:02.000Z (about 1 year ago)
- Last Synced: 2024-10-17T11:39:08.016Z (2 months ago)
- Topics: database, electron, embedded-database, indexeddb, nodejs, nosql, nosql-database, typescript
- Language: TypeScript
- Homepage:
- Size: 1.34 MB
- Stars: 28
- Watchers: 4
- Forks: 1
- Open Issues: 10
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE.md
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
# CamaDB
CamaDB is a NoSQL embedded database written in pure TypeScript for Node, Electron and browser-based environments.
[](https://github.com/semantic-release/semantic-release)
## Why?
I was struggling to find a solution for Electron-based projects that deal with larger datasets in the main thread.
- I had issues getting SQLite to work with webpack due to its native build
- SQLite doesn't (by default) return native JS data types (Dates in particular)
- Other NoSQL embedded databases seem to be largely abandoned
- Most other NoSQL embedded databases seem to be limited by V8's hard string length limits
## Goals
- Fast querying/insertion/manipulation of data, up to 1 million rows
- Frictionless integration with all JS runtimes
- Rich API
- Full TypeScript support
- Simplicity and versatility - This is built for storing data in dynamic structures
## Current state
This is still under active development and a few features are missing:
- Indexes - We're finding that this is fast even without these, but every little helps
- Rich text search
## Getting started
[Documentation](https://elmarti.github.io/camadb/classes/Collection.html)
### Installing
```
yarn add reflect-metadata
yarn add camadb
```
OR
```
npm install reflect-metadata --save
npm install camadb --save
```
### Initializing the database
All of these config options are optional:
- `path` - Where you want the data to be stored - default is `./.cama` or `cama` for indexeddb and localstorage
- `persistenceAdapter` - How you want to persist your data - `fs`, `indexeddb`, `localstorage` or `inmemory`
- `logLevel` - info or debug
```
import { Cama } from 'camadb'
const database = new Cama({
path: './.cama',
persistenceAdapter: 'fs',
logLevel: 'debug'
});
```
### Initializing a collection
- Use the columns field to add specific data types for rows. This does _need_ to be done for each column, but is essential for date objects
- Indexes aren't currently implemented, but the lookup is still very fast across 10 million rows
```
const collection = await database.initCollection('test', {
columns: [{
type:'date',
title:'date'
}],
indexes: [],
});
```
### Insert one
```
await collection.insertOne({
_id: 'test',
name: 'Dummy field',
description: `Data`,
});
```
### Insert many
```
await collection.insertMany([{
_id: 'test',
name: 'Dummy field',
description: `Data`,
}]);
```
### Find many
CamaDB uses a MongoDB style query language, powered by [SiftJS](https://github.com/crcn/sift.js/). Have a look at that project to see the full capabilities of that library.
```
const findResult = await collection.findMany({
_id: {
$gte: 50000,
},
},
{
sort:{
desc: x => x._id
},
offset: 100,
limit: 100
});
```
### Updating
Again we use a MongoDB style language for data updates, for this we use [obop](https://github.com/kawanet/obop)
```
await collection.updateMany({
_id:3
}, {
$set: {
steve:"steve"
}
});
```
### Aggregation
We use [Mingo](https://github.com/kofrasa/mingo) for aggregation - currently lookup commands aren't supported.
```
const aggregationResult = await collection.aggregate([{
$match:{
_id:3
}
}]);
```