Beyonce
A type-safe DynamoDB query builder for TypeScript.
Beyonce's features include:
-
Low boilerplate. Define your tables, partitions, indexes and models in YAML and Beyonce codegens TypeScript definitions for you.
-
Store heterogeneous models in the same table. Unlike most DynamoDB libraries, Beyonce doesn't force you into a 1 model per table paradigm. It supports storing related models in the same table partition, which allows you to "precompute joins" and retrieve those models with a single roundtrip query to the db.
-
Type-safe API. Beyonce's API is type-safe. It's aware of which models live under your partition and sort keys (even for global secondary indexes).
When you get
, batchGet
or query
, the result types are automatically inferred. And when you apply filters on your
query
the attribute names are automatically type-checked.
-
Application-level encryption. Beyonce loves Jay-Z and supports him out of the box. Combine them into
the power couple they deserve to be, and every non-key, non-index attribute on your models will be automatically encrypted before you send it to Dynamo. This grants an additional layer of security beyond just enabling AWS's DynamoDB server-side-enryption option (which you should do too).
Usage
1. Install
First install beyonce - npm install @ginger.io/beyonce
2. Define your models
Define your partitions
and models
in YAML:
Tables:
Library:
Partitions:
Author: [author, _.authorId]
Models:
Author:
partition: Author
sort: [author, _.authorId]
id: string
name: string
Book:
partition: Author
sort: [book, _.bookId]
id: string
title: string
Global secondary indexes
If your table(s) have GSI's you can specify them like this:
Tables:
Library:
Partitions:
Author: [author, _.authorId]
GSIs:
byName:
partition: name
sort: id
Note: Beyonce currently assumes that your GSI indexes project all model attributes, which will
be reflected in the return types of your queries.
External types
You can specify external types you need to import like so:
Author:
...
address: author/Address
Which transforms into import { Address } from "author/address"
3. Codegen TypeScript classes for your models, partition keys and sort keys
npx beyonce --in src/models.yaml --out src/generated/models.ts
4. Write type-safe queries
Now you can write partition-aware, type safe queries with abandon:
Get yourself a Beyonce and import the generated models, partition keys and sort keys
import { Beyonce } from "@ginger.io/beyonce"
import { DynamoDB } from "aws-sdk"
import {
Author,
author,
Book,
ModelType,
LibraryTable,
} from "generated/models"
const beyonce = new Beyonce(
LibraryTable.name,
new DynamoDB({
endpoint: "...",
region: "..."
})
)
Queries
Put
const authorModel = author({
id: "1",
name: "Jane Austin"
})
await beyonce.put(
{
partition: LibraryTable.pk.Author({ authorId: "1" }),
sort: LibraryTable.sk.Author({ authorId: "1" })
},
authorModel
)
Get
const author = await beyonce.get({
partition: LibraryTable.pk.Author({ authorId: "1" }),
sort: LibraryTable.sk.Author({ authorId: "1" })
}))
Query
const authorWithBooks = await beyonce
.query(LibraryTable.pk.Author({ authorId: "1" }))
.exec()
const authorWithFilteredBooks = await beyonce
.query(LibraryTable.pk.Author({ authorId: "1" }))
.attributeNotExists("title")
.or("title", "=", "Brave New World")
.exec()
The return types of the above queries are automatically inferred as Author | Book
. And when processing
results you can easily determine which type of model you're dealing with via the model
attribute beyonce
codegens onto your models.
authorWithBooks.forEach(authorOrBook => {
if (authorOrBook.model === ModelType.Author) {
} else if (authorOrBook.model == ModelType.Book) {
}
}
QueryGSI
const { byName } = LibraryTable.gsis
const prideAndPrejudice = await beyonce
.queryGSI(byName.name, byName.pk({ name: "Jane Austen" }))
.where("title", "=", "Pride and Prejudice")
.exec()
BatchGet
const batchResults = await beyonce.batchGet({
keys: [
{
partition: LibraryTable.pk.Author({ authorId: "1" }),
sort: LibraryTable.sk.Author({ authorId: "1" })
},
{
partition: LibraryTable.pk.Author({ authorId: "2" }),
sort: LibraryTable.sk.Author({ authorId: "2" })
},
{
partition: LibraryTable.pk.Author({ authorId: "1" }),
sort: LibraryTable.sk.Book({ bookId: "1" })
},
{
partition: LibraryTable.pk.Author({ authorId: "2" }),
sort: LibraryTable.sk.Book({ bookId: "2" })
}
]
})
Encryption
Beyonce integrates with Jay-Z to enable transparent application-layer encryption
out of the box using KMS with just a few additional lines of code:
import { KMS } from "aws-sdk"
import { KMSDataKeyProvider, JayZ } from "@ginger.io/jay-z"
const dynamo = new DynamoDB({endpoint: "...", region: "..."})
const kmsKeyId = "..."
const keyProvider = new KMSDataKeyProvider(kmsKeyId, new KMS())
const jayZ = new JayZ(keyProvider)
const beyonce = new Beyonce(
LibraryTable.name,
dynamo,
{
jayz,
encryptionBlacklist: Library.table.encryptionBlacklist
}
)
Things beyonce should do, but doesn't (yet)
- Support the full range of Dynamo filter expressions
- Support partition and sort key names other than
pk
and sk
An aside on storing heterogenous models in the same table
When using DynamoDB, you often want to "pre-compute" joins by sticking a set of heterogeneous models into the same table, under the same partition key.
This allows for retrieving related records using a single query instead of N.
Unfortunately most existing DynamoDB libraries, like DynamoDBMapper, don't support this
use case as they follow the SQL convention sticking each model into a separte table.
For example, we might want to fetch an Author
+ all their Book
s in a single query. And we'd accomplish that by sticking both models
under the same partition key - e.g. author-${id}
.
AWS's guidelines, take this to the extreme:
...most well-designed applications require only one table
Keep in mind that the primary reason they recommened this is to avoid forcing the application-layer to perform in-memory joins. Due to Amazon's scale, they are
highly motivated to minimize the number of roundtrip db calls.
You are probably not Amazon scale. And thus probably don't need to shove everything into a single table.
But you might want to keep a few related models in the same table, under the same partition key and fetch
those models in a type-safe way. Beyonce makes that easy.