DynamoDB Toolbox
Single Table Designs have never been this easy!
The DynamoDB Toolbox is a set of tools that makes it easy to work with Amazon DynamoDB and the DocumentClient. It's designed with Single Tables in mind, but works just as well with multiple tables. It lets you define your Entities (with typings and aliases) and map them to your DynamoDB tables. You can then generate the API parameters to put
, get
, delete
, update
, query
, scan
, batchGet
, and batchWrite
data by passing in JavaScript objects. The DynamoDB Toolbox will map aliases, validate and coerce types, and even write complex UpdateExpression
s for you. 😉
Why single table design?
Learn more about single table design in Alex Debrie's blog.
Version 0.9 🙌
Feedback is welcome and much appreciated! (Huge thanks to @ThomasAribart for all his work on this 🙌)
Using AWS SDK v2?
dynamodb-toolbox@v0.8 and above is using AWS SDK v3. If you are using AWS SDK v2, please use versions that are lower than 0.8.
Docs & Community
Quick Start
Using your favorite package manager, install DynamoDB Toolbox and the aws-sdk v3 dependencies in your project by running one of the following commands:
# npm
npm i dynamodb-toolbox
npm install @aws-sdk/lib-dynamodb @aws-sdk/client-dynamodb
# yarn
yarn add dynamodb-toolbox
yarn add @aws-sdk/lib-dynamodb @aws-sdk/client-dynamodb
Require or import Table
and Entity
from dynamodb-toolbox
:
import { Table, Entity } from 'dynamodb-toolbox'
Create a Table (with the DocumentClient using aws-sdk v3):
import { DynamoDBClient } from '@aws-sdk/client-dynamodb'
import { DynamoDBDocumentClient } from '@aws-sdk/lib-dynamodb'
const marshallOptions = {
// Whether to automatically convert empty strings, blobs, and sets to `null`.
convertEmptyValues: false, // if not false explicitly, we set it to true.
// Whether to remove undefined values while marshalling.
removeUndefinedValues: false, // false, by default.
// Whether to convert typeof object to map attribute.
convertClassInstanceToMap: false, // false, by default.
}
const unmarshallOptions = {
// Whether to return numbers as a string instead of converting them to native JavaScript numbers.
// NOTE: this is required to be true in order to use the bigint data type.
wrapNumbers: false, // false, by default.
}
const translateConfig = { marshallOptions, unmarshallOptions }
// Instantiate a DocumentClient
export const DocumentClient = DynamoDBDocumentClient.from(new DynamoDBClient({}), translateConfig)
// Instantiate a table
const MyTable = new Table({
// Specify table name (used by DynamoDB)
name: 'my-table',
// Define partition and sort keys
partitionKey: 'pk',
sortKey: 'sk',
// Add the DocumentClient
DocumentClient
})
Create an Entity:
const Customer = new Entity({
// Specify entity name
name: 'Customer',
// Define attributes
attributes: {
id: { partitionKey: true }, // flag as partitionKey
sk: { hidden: true, sortKey: true }, // flag as sortKey and mark hidden
age: { type: 'number' }, // set the attribute type
name: { type: 'string', map: 'data' }, // map 'name' to table attribute 'data'
emailVerified: { type: 'boolean', required: true }, // specify attribute as required
co: { alias: 'company' }, // alias table attribute 'co' to 'company'
status: ['sk', 0], // composite key mapping
date_added: ['sk', 1] // composite key mapping
},
// Assign it to our table
table: MyTable
// In Typescript, the "as const" statement is needed for type inference
} as const)
Put an item:
// Create an item (using table attribute names or aliases)
const customer = {
id: 123,
age: 35,
name: 'Jane Smith',
emailVerified: true,
company: 'ACME',
status: 'active',
date_added: '2020-04-24'
}
// Use the 'put' method of Customer:
await Customer.put(customer)
The item will be saved to DynamoDB like this:
{
"pk": 123,
"sk": "active#2020-04-24",
"age": 35,
"data": "Jane Smith",
"emailVerified": true,
"co": "ACME",
// Attributes auto-generated by DynamoDB-Toolbox
"_et": "customer", // Entity name (required for parsing)
"_ct": "2021-01-01T00:00:00.000Z", // Item creation date (optional)
"_md": "2021-01-01T00:00:00.000Z" // Item last modification date (optional)
}
You can then get the data:
// Specify primary key
const primaryKey = {
id: 123,
status: 'active',
date_added: '2020-04-24'
}
// Use the 'get' method of Customer
const response = await Customer.get(primaryKey)
Since v0.4, the method inputs, options and response types are inferred from the Entity definition:
await Customer.put({
id: 123,
// ❌ Sort key is required ("sk" or both "status" and "date_added")
age: 35,
name: ['Jane', 'Smith'], // ❌ name should be a string
emailVerified: undefined, // ❌ attribute is marked as required
company: 'ACME'
})
const { Item: customer } = await Customer.get({
id: 123,
status: 'active',
date_added: '2020-04-24' // ✅ Valid primary key
})
type Customer = typeof customer
// 🙌 Type is equal to:
type ExpectedCustomer =
| {
id: any
age?: number | undefined
name?: string | undefined
emailVerified: boolean
company?: any
status: any
date_added: any
entity: string
created: string
modified: string
}
| undefined
See Type Inference in the documentation for more details.
Features
- Table Schemas and DynamoDB Typings: Define your Table and Entity data models using a simple JavaScript object structure, assign DynamoDB data types, and optionally set defaults.
-
Magic UpdateExpressions: Writing complex
UpdateExpression
strings is a major pain, especially if the input data changes the underlying clauses or requires dynamic (or nested) attributes. This library handles everything from simpleSET
clauses, to complexlist
andset
manipulations, to defaulting values with smartly appliedif_not_exists()
to avoid overwriting data. -
Bidirectional Mapping and Aliasing: When building a single table design, you can define multiple entities that map to the same table. Each entity can reuse fields (like
pk
andsk
) and map them to different aliases depending on the item type. Your data is automatically mapped correctly when reading and writing data. -
Composite Key Generation and Field Mapping: Doing some fancy data modeling with composite keys? Like setting your
sortKey
to[country]#[region]#[state]#[county]#[city]#[neighborhood]
model hierarchies? DynamoDB Toolbox lets you map data to these composite keys which will both autogenerate the value and parse them into fields for you. -
Type Coercion and Validation: Automatically coerce values to strings, numbers and booleans to ensure consistent data types in your DynamoDB tables. Validate
list
,map
, andset
types against your data. Oh yeah, andset
s are automatically handled for you. 😉 -
Powerful Query Builder: Specify a
partitionKey
, and then easily configure your sortKey conditions, filters, and attribute projections to query your primary or secondary indexes. This library can even handle pagination with a simple.next()
method. -
Simple Table Scans: Scan through your table or secondary indexes and add filters, projections, parallel scans and more. And don't forget the pagination support with
.next()
. -
Filter and Condition Expression Builder: Build complex Filter and Condition expressions using a standardized
array
andobject
notation. No more appending strings! - Projection Builder: Specify which attributes and paths should be returned for each entity type, and automatically filter the results.
- Secondary Index Support: Map your secondary indexes (GSIs and LSIs) to your table, and dynamically link your entity attributes.
- Batch Operations: Full support for batch operations with a simpler interface to work with multiple entities and tables.
- Transactions: Full support for transaction with a simpler interface to work with multiple entities and tables.
- Default Value Dependency Graphs: Create dynamic attribute defaults by chaining other dynamic attribute defaults together.
- TypeScript Support: v0.4 of this library provides strong typing support AND type inference 😍. Inferred type can still overriden with Overlays. Some Utility Types are also exposed. Additional work is still required to support schema validation & typings.
Additional References
Contributions and Feedback
Contributions, ideas and bug reports are welcome and greatly appreciated. Please add issues for suggestions and bug reports or create a pull request. You can also contact me on Twitter: @jeremy_daly.