Simple to use local JSON database. Use native JavaScript API to query. Written in TypeScript. ๐ฆ
// Edit db.json content using native JS API
db.data
.posts
.push({ id: 1, title: 'lowdb is awesome' })
// Save to file
db.write()
// db.json
{
"posts": [
{ "id": 1, "title": "lowdb is awesome" }
]
}
If you like lowdb, see also xv (test runner) and steno (fast file writer).
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- Lightweight
- Minimalist
- TypeScript
- plain JS
- Atomic write
- Hackable:
- Change storage, file format (JSON, YAML, ...) or add encryption via adapters
- Add lodash, ramda, ... for super powers!
npm install lowdb
Lowdb is a pure ESM package. If you're having trouble using it in your project, please read this.
Next.js: there's a known issue. Until it's fixed, please use this workaround or lowdb ^4.0.0
.
// Remember to set type: module in package.json or use .mjs extension
import { join, dirname } from 'node:path'
import { fileURLToPath } from 'node:url'
import { Low } from 'lowdb'
import { JSONFile } from 'lowdb/node'
// File path
const __dirname = dirname(fileURLToPath(import.meta.url));
const file = join(__dirname, 'db.json')
// Configure lowdb to write to JSONFile
const adapter = new JSONFile(file)
const db = new Low(adapter)
// Read data from JSON file, this will set db.data content
await db.read()
// If db.json doesn't exist, db.data will be null
// Use the code below to set default data
// db.data = db.data || { posts: [] } // For Node < v15.x
db.data ||= { posts: [] } // For Node >= 15.x
// Create and query items using native JS API
db.data.posts.push('hello world')
const firstPost = db.data.posts[0]
// Alternatively, you can also use this syntax if you prefer
const { posts } = db.data
posts.push('hello world')
// Finally write db.data content to file
await db.write()
// db.json
{
"posts": [ "hello world" ]
}
You can use TypeScript to check your data types.
type Data = {
words: string[]
}
const adapter = new JSONFile<Data>('db.json')
const db = new Low(adapter)
db.data
.words
.push('foo') // โ
Success
db.data
.words
.push(1) // โ TypeScript error
You can also add lodash or other utility libraries to improve lowdb.
import lodash from 'lodash'
type Post = {
id: number;
title: string;
}
type Data = {
posts: Post[]
}
// Extend Low class with a new `chain` field
class LowWithLodash<T> extends Low<T> {
chain: lodash.ExpChain<this['data']> = lodash.chain(this).get('data')
}
const adapter = new JSONFile<Data>('db.json')
const db = new LowWithLodash(adapter)
await db.read()
// Instead of db.data use db.chain to access lodash API
const post = db.chain
.get('posts')
.find({ id: 1 })
.value() // Important: value() must be called to execute chain
See examples/
directory.
Lowdb has two classes (for asynchronous and synchronous adapters).
import { Low } from 'lowdb'
import { JSONFile } from 'lowdb/node'
const db = new Low(new JSONFile('file.json'))
await db.read()
await db.write()
import { LowSync } from 'lowdb'
import { JSONFileSync } from 'lowdb/node'
const db = new LowSync(new JSONFileSync('file.json'))
db.read()
db.write()
Calls adapter.read()
and sets db.data
.
Note: JSONFile
and JSONFileSync
adapters will set db.data
to null
if file doesn't exist.
db.data // === null
db.read()
db.data // !== null
Calls adapter.write(db.data)
.
db.data = { posts: [] }
db.write() // file.json will be { posts: [] }
db.data = {}
db.write() // file.json will be {}
Holds your db content. If you're using the adapters coming with lowdb, it can be any type supported by JSON.stringify
.
For example:
db.data = 'string'
db.data = [1, 2, 3]
db.data = { key: 'value' }
Adapters for reading and writing JSON files.
import { JSONFile, JSONFileSync } from 'lowdb/node'
new Low(new JSONFile(filename))
new LowSync(new JSONFileSync(filename))
In-memory adapters. Useful for speeding up unit tests. See examples/
directory.
import { Memory, MemorySync } from 'lowdb'
new Low(new Memory())
new LowSync(new MemorySync())
Synchronous adapter for window.localStorage
and window.sessionStorage
.
import { LocalStorage, SessionStorage } from 'lowdb/browser'
new LowSync(new LocalStorage(name))
new LowSync(new SessionStorage(name))
Adapters for reading and writing text. Useful for creating custom adapters.
If you've published an adapter for lowdb, feel free to create a PR to add it here.
You may want to create an adapter to write db.data
to YAML, XML, encrypt data, a remote storage, ...
An adapter is a simple class that just needs to expose two methods:
class AsyncAdapter {
read() { /* ... */ } // should return Promise<data>
write(data) { /* ... */ } // should return Promise<void>
}
class SyncAdapter {
read() { /* ... */ } // should return data
write(data) { /* ... */ } // should return nothing
}
For example, let's say you have some async storage and want to create an adapter for it:
import { api } from './AsyncStorage'
class CustomAsyncAdapter {
// Optional: your adapter can take arguments
constructor(args) {
// ...
}
async read() {
const data = await api.read()
return data
}
async write(data) {
await api.write(data)
}
}
const adapter = new CustomAsyncAdapter()
const db = new Low(adapter)
See src/adapters/
for more examples.
To create an adapter for another format than JSON, you can use TextFile
or TextFileSync
.
For example:
import { Adapter, Low } from 'lowdb'
import { TextFile } from 'lowdb/node'
import YAML from 'yaml'
class YAMLFile {
constructor(filename) {
this.adapter = new TextFile(filename)
}
async read() {
const data = await this.adapter.read()
if (data === null) {
return null
} else {
return YAML.parse(data)
}
}
write(obj) {
return this.adapter.write(YAML.stringify(obj))
}
}
const adapter = new YAMLFile('file.yaml')
const db = new Low(adapter)
Lowdb doesn't support Node's cluster module.
If you have large JavaScript objects (~10-100MB
) you may hit some performance issues. This is because whenever you call db.write
, the whole db.data
is serialized using JSON.stringify
and written to storage.
Depending on your use case, this can be fine or not. It can be mitigated by doing batch operations and calling db.write
only when you need it.
If you plan to scale, it's highly recommended to use databases like PostgreSQL or MongoDB instead.