electrodb
Advanced tools
A library to more easily create and interact with multiple entities and heretical relationships in dynamodb
ElectroDB is a DynamoDB library that simplifies the process of defining and interacting with DynamoDB tables. It provides a high-level abstraction for defining entities, managing relationships, and performing CRUD operations, making it easier to work with DynamoDB's complex data modeling and querying capabilities.
Entity Definition
This feature allows you to define an entity with its attributes and indexes. The code sample demonstrates how to create a User entity with attributes like userId, name, and email, and a primary index.
const { Entity } = require('electrodb');
const UserEntity = new Entity({
model: {
entity: 'User',
version: '1',
service: 'UserService'
},
attributes: {
userId: { type: 'string', required: true },
name: { type: 'string', required: true },
email: { type: 'string', required: true }
},
indexes: {
primary: {
pk: { field: 'pk', composite: ['userId'] },
sk: { field: 'sk', composite: [] }
}
}
});CRUD Operations
This feature provides methods for performing CRUD operations on the defined entities. The code sample shows how to create, read, update, and delete a user entity.
const user = await UserEntity.put({
userId: '123',
name: 'John Doe',
email: 'john.doe@example.com'
}).go();
const fetchedUser = await UserEntity.get({ userId: '123' }).go();
const updatedUser = await UserEntity.update({ userId: '123' })
.set({ name: 'Jane Doe' })
.go();
const deletedUser = await UserEntity.delete({ userId: '123' }).go();Querying
This feature allows you to perform complex queries on your entities. The code sample demonstrates how to query the User entity using the primary index.
const users = await UserEntity.query.primary({ userId: '123' }).go();Relationships
This feature allows you to define and manage relationships between different entities. The code sample shows how to fetch a user along with their related orders using the Service class.
const { Service } = require('electrodb');
const UserService = new Service({
User: UserEntity,
Order: OrderEntity
});
const userWithOrders = await UserService.User.get({ userId: '123' }).include(OrderEntity).go();DynamoDB Toolbox is a set of tools that makes it easier to work with Amazon DynamoDB. It provides a simple and consistent way to define and interact with DynamoDB tables and items. Compared to ElectroDB, DynamoDB Toolbox offers a more lightweight and flexible approach but may require more manual setup for complex data models.
The AWS SDK for JavaScript provides a comprehensive set of tools for interacting with AWS services, including DynamoDB. While it offers low-level access to DynamoDB's API, it lacks the high-level abstractions and convenience features provided by ElectroDB, making it more suitable for developers who need fine-grained control over their DynamoDB interactions.
Dynogels is a DynamoDB data mapper for Node.js that simplifies the process of defining and interacting with DynamoDB tables. It offers a similar high-level abstraction as ElectroDB but is less actively maintained and may not support some of the latest DynamoDB features.
ElectroDB is a dynamodb library to ease the use of having multiple entities and complex hierarchical relationships in a single dynamodb table.
This library is a work in progress, please submit issues/feedback or reach out on twitter @tinkertamper.
ExpressionAttributeNames, ExpressionAttributeValues.Turn this:
MallStores.query
.leases({ mallId: "EastPointe" })
.between({ leaseEndDate: "2020-04-01" }, { leaseEndDate: "2020-07-01" })
.filter(({rent, discount}) => `
${rent.between("2000.00", "5000.00")} AND ${discount.lte("1000.00")}
`)
.params();
Into This:
{
"IndexName": "idx2",
"TableName": "electro",
"ExpressionAttributeNames": {
"#rent": "rent",
"#discount": "discount",
"#pk": "idx2pk",
"#sk1": "idx2sk"
},
"ExpressionAttributeValues": {
":rent1": "2000.00",
":rent2": "5000.00",
":discount1": "1000.00",
":pk": "$mallstoredirectory_1#mallid_eastpointe",
":sk1": "$mallstore#leaseenddate_2020-04-01#rent_",
":sk2": "$mallstore#leaseenddate_2020-07-01#rent_"
},
"KeyConditionExpression": "#pk = :pk and #sk1 BETWEEN :sk1 AND :sk2",
"FilterExpression": "(#rent between :rent1 and :rent2) AND #discount <= :discount1"
}
Install from NPM
npm install electrodb --save
Require or import Entity or Service from electrodb:
const {Entity, Service} = require("electrodb");
To see full examples of ElectroDB in action, go to the Examples section.
Entity allows you to create separate and individual business objects in a DynamoDB table. When queried your results will not include other Entities that exist the same table. For more detail, read Entities.
Service allows you to build a relationships across Entities. A service imports Entity Models, builds individual Entities and builds Collections for cross Entity querying. For more detail, read Services.
You can use Entities independent of Services, you do not need to import models into a Service to use them individually. However, you do you need to use a Service if you intend make queries join multiple Entities.
In ElectroDB an Entity is represents a single business object. For example, in a simple task tracking application, one Entity could represent an Employee and another Entity might represent a the Task that the employee is assigned to.
Require or import Entity from electrodb:
const {Entity} = require("electrodb");
In ElectroDB a Service represents a collection of Entities and also allows you to build queries span across Entities. Similar to Entities, Services can coexist on a single table without collision. You can use Entities independent of Services, you do not need to import models into a Service to use them individually. However, you do you need to use a Service if you intend make queries join multiple Entities.
Require or import Service from electrodb:
const {Service} = require("electrodb");
Create an Entity's schema. In the below example.
const DynamoDB = require("aws-sdk/clients/dynamodb");
const {Entity, Service} = require("electrodb");
const client = new DynamoDB.DocumentClient();
const EmployeesModel = {
entity: "employees",
version: "1",
service: "taskapp",
table: "projectmanagement",
attributes: {
employee: {
type: "string",
default: () => uuidv4(),
},
firstName: {
type: "string",
required: true,
},
lastName: {
type: "string",
required: true,
},
office: {
type: "string",
required: true,
},
title: {
type: "string",
required: true,
},
team: {
type: ["development", "marketing", "finance", "product", "cool cats and kittens"],
required: true,
},
salary: {
type: "string",
required: true,
},
manager: {
type: "string",
},
dateHired: {
type: "string",
validate: /^\d{4}-\d{2}-\d{2}$/gi
},
birthday: {
type: "string",
validate: /^\d{4}-\d{2}-\d{2}$/gi
},
},
indexes: {
employee: {
pk: {
field: "pk",
facets: ["employee"],
},
sk: {
field: "sk",
facets: [],
},
},
coworkers: {
index: "gsi1pk-gsi1sk-index",
collection: "workplaces",
pk: {
field: "gsi1pk",
facets: ["office"],
},
sk: {
field: "gsi1sk",
facets: ["team", "title", "employee"],
},
},
teams: {
index: "gsi2pk-gsi2sk-index",
pk: {
field: "gsi2pk",
facets: ["team"],
},
sk: {
field: "gsi2sk",
facets: ["title", "salary", "employee"],
},
},
employeeLookup: {
collection: "assignments",
index: "gsi3pk-gsi3sk-index",
pk: {
field: "gsi3pk",
facets: ["employee"],
},
sk: {
field: "gsi3sk",
facets: [],
},
},
roles: {
index: "gsi4pk-gsi4sk-index",
pk: {
field: "gsi4pk",
facets: ["title"],
},
sk: {
field: "gsi4sk",
facets: ["salary", "employee"],
},
},
directReports: {
index: "gsi5pk-gsi5sk-index",
pk: {
field: "gsi5pk",
facets: ["manager"],
},
sk: {
field: "gsi5sk",
facets: ["team", "office", "employee"],
},
},
},
filters: {
upcomingCelebrations: (attributes, startDate, endDate) => {
let { dateHired, birthday } = attributes;
return `${dateHired.between(startDate, endDate)} OR ${birthday.between(
startDate,
endDate,
)}`;
},
},
};
const TasksModel = {
entity: "tasks",
version: "1",
service: "taskapp",
table: "projectmanagement",
attributes: {
task: {
type: "string",
default: () => uuidv4(),
},
project: {
type: "string",
},
employee: {
type: "string",
},
description: {
type: "string",
},
},
indexes: {
task: {
pk: {
field: "pk",
facets: ["task"],
},
sk: {
field: "sk",
facets: ["project", "employee"],
},
},
project: {
index: "gsi1pk-gsi1sk-index",
pk: {
field: "gsi1pk",
facets: ["project"],
},
sk: {
field: "gsi1sk",
facets: ["employee", "task"],
},
},
assigned: {
collection: "assignments",
index: "gsi3pk-gsi3sk-index",
pk: {
field: "gsi3pk",
facets: ["employee"],
},
sk: {
field: "gsi3sk",
facets: ["project", "task"],
},
},
},
};
Create individual Entities with the Models or join them via a Service:
// Independent Models
let employees = new Entity(EmployeesModel, { client });
let tasks = new Entity(TasksModel, { client });
// Joined via a Service
let TaskApp = new Service({
version: "1",
service: "TaskApp",
table: "projectmanagement",
},
{ client },
);
TaskApp.join(EmployeesModel); // TaskApp.entities.employees
TaskApp.join(TasksModel); // TaskApp.entities.tasks
| Property | Description |
|---|---|
| service | Name of the application using the entity, used to namespace all entities |
| entity | Name of the entity that the schema represents |
| table | Name of the dynamodb table in aws |
| version | (optional) The version number of the schema, used to namespace keys |
| attributes | An object containing each attribute that makes up the schema |
| indexes | An object containing table indexes, including the values for the table's default Partition Key and Sort Key |
| filters | An object containing user defined filter template functions. |
| Property | Description |
|---|---|
| service | Name of the service, used to namespace all joined entities, will override the model definition. |
| table | Name of the dynamodb table in aws, will override the model definition. |
| version | (optional) The version number of the schema, used to namespace keys, will override the model definition. |
Optional second parameter
| Property | Description |
|---|---|
| client | (optional) A docClient instance for use when querying a DynamoDB table. This is optional if you wish to only use the params functionality, but required if you actually need to query against a database. |
Attributes define an Entity record. The propertyName represents the value your code will use to represent an attribute.
Pro-Tip: Using the
fieldproperty, you can map anAttributeNameto a different field name in your table. This can be useful to utilize existing tables, existing models, or even to reduce record sizes via shorter field names.
attributes: {
<AttributeName>: {
"type": string|string[],
"required"?: boolean,
"default"?: value|() => value
"validate"?: RegExp|() => boolean
"field"?: string
"readOnly"?: boolean
"label"?: string
"cast"?: "number"|"string"|"boolean",
"get"?: (attribute, schema) => value,
"set"?: (attribute, schema) => value
}
}
| Property | Type | Required | Description |
|---|---|---|---|
type | string, string[] | yes | Accepts the values: "string", "number" "boolean", or an array of strings representing a finite list of acceptable values: ["option1", "option2", "option3"]. |
required | boolean | no | Whether or not the value is required when creating a new record. |
default | value, () => value | no | Either the default value itself or a synchronous function that returns the desired value. |
validate | RegExp, () => boolean | no | Either regex or a synchronous callback to return a boolean. |
field | string | no | The name of the attribute as it exists dynamo, if named differently in the schema attributes. Defaults to the AttributeName as defined in the schema. |
readOnly | boolean | no | Prevents update of the property after the record has been created. Attributes used in the composition of the table's primary Partition Key and Sort Key are by read-only by default. |
label | string | no | Used in index composition to prefix key facets. By default, the AttributeName is used as the label. |
cast | "number", "string", "boolean" | no | Optionally cast attribute values when interacting with DynamoDB. Current options include: "number", "string", and "boolean". |
set | (attribute, schema) => value | no | A synchronous callback allowing you apply changes to a value before it is set in params or applied to the database. First value represents the value passed to ElectroDB, second value are the attributes passed on that update/put |
get | (attribute, schema) => value | no | A synchronous callback allowing you apply changes to a value after it is retrieved from the database. First value represents the value passed to ElectroDB, second value are the attributes retrieved from the database. |
The indexes object requires at least the definition of the table's natural Partition Key and (if applicable) Sort Key.
Indexes are defined, and later referenced by their accessPatternName. These defined via a facets array that is made up of attributes names as listed the model.
indexes: {
<accessPatternName>: {
"pk": {
"field": <string>
"facets": <AttributeName[]>
},
"sk"?: {
"field": <string>
"facets": <AttributesName[]>
},
"index"?: string
"collection"?: string
}
}
| Property | Type | Required | Description |
|---|---|---|---|
pk | object | yes | Configuration for the pk of that index or table |
pk.facets | boolean | no | An array that represents the order in which attributes are concatenated to facets the key (see Facets below for more on this functionality). |
pk.field | string | yes | The name of the attribute as it exists dynamo, if named differently in the schema attributes. |
sk | object | no | Configuration for the sk of that index or table |
sk.facets | `array | string` | no |
sk.field | string | yes | The name of the attribute as it exists dynamo, if named differently in the schema attributes. |
index | string | no | Required when the Index defined is a Secondary Index; but is left blank for the table's primary index. |
collection | string | no | Used when models are joined to a Service. When two entities share a collection on the same index, they can be queried with one request to DynamoDB. The name of the collection should represent what the query would return as a pseudo Entity. (see Collections below for more on this functionality). |
A Facet is a segment of a key based on one of the attributes. Facets are concatenated together from either a Partition Key or an Sort Key key, which define an index.
There are two ways to provide facets:
For example, in the following Access Pattern, "locations" is made up of the facets storeId, mallId, buildingId and unitId which map to defined attributes in the schema:
// Input
{
storeId: "STOREVALUE",
mallId: "MALLVALUE",
buildingId: "BUILDINGVALUE",
unitId: "UNITVALUE"
};
// Output:
{
pk: '$mallstoredirectory_1#storeId_storevalue',
sk: '$mallstores#mallid_mallvalue#buildingid_buildingvalue#unitid_unitvalue'
}
For PK values, the service and version values from the model are prefixed onto the key.
For SK values, the entity value from the model is prefixed onto the key.
In a Facet Array, each element is the name of the corresponding Attribute defined in the Model. If the Attribute has a label property, that will be used to prefix the facets, otherwise the full Attribute name will be used.
attributes: {
storeId: {
type: "string",
label: "sid",
},
mallId: {
type: "string",
label: "mid",
},
buildingId: {
type: "string",
label: "bid",
},
unitId: {
type: "string",
label: "uid",
}
},
indexes: {
locations: {
pk: {
field: "pk",
facets: ["storeId"]
},
sk: {
field: "sk",
facets: ["mallId", "buildingId", "unitId"]
}
}
}
// Input
{
storeId: "STOREVALUE",
mallId: "MALLVALUE",
buildingId: "BUILDINGVALUE",
unitId: "UNITVALUE"
};
// Output:
{
pk: '$mallstoredirectory_1#sid_storevalue',
sk: '$mallstores#mid_mallvalue#bid_buildingvalue#uid_unitvalue'
}
In a Facet Template, you provide a formatted template for ElectroDB to use when making keys. Facet Templates allow for potential ElectroDB adoption on already established tables and records.
Attributes are identified by a prefixed colon and the attributes name. For example, the syntax :storeId will matches storeId attribute in the model.
Convention for a composing a key use the # symbol to separate attributes, and for labels to attach with underscore. For example, when composing both the mallId and buildingId would be expressed as mid_:mallId#bid_:buildingId.
ElectroDB will not prefix templated keys with the Entity, Project, Version, or Collection. This will give you greater control of your keys but will limit ElectroDB's ability to prevent leaking entities with some queries.
Facet Templates have some "gotchas" to consider:
1. Keys only allow for one instance of an attribute, the template :prop1#:prop1 will be interpreted the same as :prop1#.
2. ElectoDB will continue to always add a trailing delimiter to facets with keys are partially supplied. (More documentation coming on this soon)
attributes: {
storeId: {
type: "string"
},
mallId: {
type: "string"
},
buildingId: {
type: "string"
},
unitId: {
type: "string"
}
},
indexes: {
locations: {
pk: {
field: "pk",
facets: "sid_:storeId"
},
sk: {
field: "sk",
facets: "mid_:mallId#bid_:buildingId#uid_:unitId"
}
}
}
// Input
{
storeId: "STOREVALUE",
mallId: "MALLVALUE",
buildingId: "BUILDINGVALUE",
unitId: "UNITVALUE"
};
// Output:
{
pk: 'sid_storevalue',
sk: 'mid_mallvalue#bid_buildingvalue#uid_unitvalue'
}
A Collection is a grouping of Entities with the same Partition Key and allows you to make efficient query across multiple entities. If you background is SQL, imagine Partition Keys as Foreign Keys, a Collection represents a View with multiple joined Entities.
Collections are defined on an Index, and the name of the collection should represent what the query would return as a pseudo Entity.
Note:
collectionshould be unique to a single common index across entities.
Using the TaskApp Models defined in Models, these models share a collection called assignments on the index gsi3pk-gsi3sk-index
let TaskApp = new Service({
version: "1",
service: "TaskApp",
table: "projectmanagement"
}, { client });
TaskApp.join(EmployeesModel); // TaskApp.entities.employees
TaskApp.join(TasksModel); // TaskApp.entities.tasks
TaskApp.collections.assignments({employee: "JExotic"}).params();
// Results
{
TableName: 'projectmanagement',
ExpressionAttributeNames: { '#pk': 'gsi3pk', '#sk1': 'gsi3sk' },
ExpressionAttributeValues: { ':pk': '$taskapp_1#employee_joeexotic', ':sk1': '$assignments' },
KeyConditionExpression: '#pk = :pk and begins_with(#sk1, :sk1)',
IndexName: 'gsi3pk-gsi3sk-index'
}
Building thoughtful indexes can make queries simple and performant. Sometimes you need to filter results down further. By adding Filters to your model, you can extend your queries with custom filters. Below is the traditional way you would add a filter to Dynamo's DocumentClient directly along side how you would accomplish the same using a Filter function.
{
IndexName: 'idx2',
TableName: 'electro',
ExpressionAttributeNames: {
'#rent': 'rent',
'#discount': 'discount',
'#pk': 'idx2pk',
'#sk1': 'idx2sk'
},
ExpressionAttributeValues: {
':rent1': '2000.00',
':rent2': '5000.00',
':discount1': '1000.00',
':pk': '$mallstoredirectory_1#mallid_eastpointe',
':sk1': '$mallstore#leaseenddate_2020-04-01#rent_',
':sk2': '$mallstore#leaseenddate_2020-07-01#rent_'
},
KeyConditionExpression: '#pk = :pk and #sk1 BETWEEN :sk1 AND :sk2',
FilterExpression: '(#rent between :rent1 and :rent2) AND #discount <= :discount1'
}
/**
* Filter by low rent a specific mall or a leaseEnd withing a specific range
* @param {Object} attributes - All attributes from the model with methods for each filter operation
* @param {...*} values - Values passed when calling the filter in a query chain.
**/
filters: {
rentPromotions: function(attributes, minRent, maxRent, promotion) {
let {rent, discount} = attributes;
return `
${rent.between(minRent, maxRent)} AND ${discount.lte(promotion)}
`
}
}
let MallStores = new Entity("MallStores", model);
let maxRent = "5000.00";
let minRent = "2000.00";
let promotion = "1000.00";
let stores = MallStores.query
.stores({ mallId: "EastPointe" })
.between({ leaseEndDate: "2020-04-01" }, { leaseEndDate: "2020-07-01" })
.rentPromotions(minRent, maxRent, promotion)
.params();
// Results
{
IndexName: 'idx2',
TableName: 'electro',
ExpressionAttributeNames: {
'#rent': 'rent',
'#discount': 'discount',
'#pk': 'idx2pk',
'#sk1': 'idx2sk'
},
ExpressionAttributeValues: {
':rent1': '2000.00',
':rent2': '5000.00',
':discount1': '1000.00',
':pk': '$mallstoredirectory_1#mallid_eastpointe',
':sk1': '$mallstore#leaseenddate_2020-04-01#rent_',
':sk2': '$mallstore#leaseenddate_2020-07-01#rent_'
},
KeyConditionExpression: '#pk = :pk and #sk1 BETWEEN :sk1 AND :sk2',
FilterExpression: '(#rent between :rent1 and :rent2) AND #discount <= :discount1'
}
let MallStores = new Entity("MallStores", model);
let maxRent = "5000.00";
let minRent = "2000.00";
let promotion = "1000.00";
let stores = MallStores.query
.leases({ mallId: "EastPointe" })
.between({ leaseEndDate: "2020-04-01" }, { leaseEndDate: "2020-07-01" })
.filter(({rent, discount}) => `
${rent.between(minRent, maxRent)} AND ${discount.lte(promotion)}
`)
.params();
// Results
{
IndexName: 'idx2',
TableName: 'electro',
ExpressionAttributeNames: {
'#rent': 'rent',
'#discount': 'discount',
'#pk': 'idx2pk',
'#sk1': 'idx2sk'
},
ExpressionAttributeValues: {
':rent1': '2000.00',
':rent2': '5000.00',
':discount1': '1000.00',
':pk': '$mallstoredirectory_1#mallid_eastpointe',
':sk1': '$mallstore#leaseenddate_2020-04-01#rent_',
':sk2': '$mallstore#leaseenddate_2020-07-01#rent_'
},
KeyConditionExpression: '#pk = :pk and #sk1 BETWEEN :sk1 AND :sk2',
FilterExpression: '(#rent between :rent1 and :rent2) AND #discount <= :discount1'
}
Filter functions allow you to write a FilterExpression without having to worry about the complexities of expression attributes. To accomplish this, ElectroDB injects an object attributes as the first parameter to all Filter Functions. This object contains every Attribute defined in the Entity's Model with the following operators as methods:
| operator | example | result |
|---|---|---|
gte | rent.gte(maxRent) | #rent >= :rent1 |
gt | rent.gt(maxRent) | #rent > :rent1 |
lte | rent.lte(maxRent) | #rent <= :rent1 |
lt | rent.lt(maxRent) | #rent < :rent1 |
eq | rent.eq(maxRent) | #rent = :rent1 |
begins | rent.begins(maxRent) | begins_with(#rent, :rent1) |
exists | rent.exists() | attribute_exists(#rent) |
notExists | rent.notExists() | attribute_not_exists(#rent) |
contains | rent.contains(maxRent) | contains(#rent = :rent1) |
notContains | rent.notContains(maxRent) | not contains(#rent = :rent1) |
between | rent.between(minRent, maxRent) | (#rent between :rent1 and :rent2) |
name | rent.name() | #rent |
value | rent.value(maxRent) | :rent1 |
This functionality allows you to write the remaining logic of your FilterExpression with ease. Add complex nested and/or conditions or other FilterExpression logic while ElectroDB handles the ExpressionAttributeNames and ExpressionAttributeValues.
It is possible to include chain multiple filters. The resulting FilterExpressions are concatinated with an implicit AND operator.
let MallStores = new Entity("MallStores", model);
let stores = MallStores.query
.leases({ mallId: "EastPointe" })
.between({ leaseEndDate: "2020-04-01" }, { leaseEndDate: "2020-07-01" })
.filter(({ rent, discount }) => `
${rent.between("2000.00", "5000.00")} AND ${discount.eq("1000.00")}
`)
.filter(({ category }) => `
${category.eq("food/coffee")}
`)
.params();
// Results
{
TableName: 'StoreDirectory',
ExpressionAttributeNames: {
'#rent': 'rent',
'#discount': 'discount',
'#category': 'category',
'#pk': 'idx2pk',
'#sk1': 'idx2sk'
},
ExpressionAttributeValues: {
':rent1': '2000.00',
':rent2': '5000.00',
':discount1': '1000.00',
':category1': 'food/coffee',
':pk': '$mallstoredirectory_1#mallid_eastpointe',
':sk1': '$mallstore#leaseenddate_2020-04-01#storeid_',
':sk2': '$mallstore#leaseenddate_2020-07-01#storeid_'
},
KeyConditionExpression: '#pk = :pk and #sk1 BETWEEN :sk1 AND :sk2',
IndexName: 'idx2',
FilterExpression: '(#rent between :rent1 and :rent2) AND (#discount = :discount1 AND #category = :category1)'
}
Forming a composite Partition Key and Sort Key is a critical step in planning Access Patterns in DynamoDB. When planning composite keys, it is critical to consider the order in which they are composed. As of the time of writing this documentation, DynamoDB has the following constraints that should be taken into account when planning your Access Patterns:
begins_with, between, >, >=, <, <=, and Equals.| operator | use case |
|---|---|
begins_with | Keys starting with a particular set of characters. |
between | Keys between a specified range. |
eq | Keys equal to some value |
gt | Keys less than some value |
gte | Keys less than or equal to some value |
lt | Keys greater than some value |
lte | Keys greater than or equal to some value |
Carefully considering your Facet order will allow *ElectroDB to express hierarchical relationships and unlock more available Access Patterns for your application.
For example, let's say you have a MallStore Entity that represents Store Locations inside Malls:
let model = {
service: "MallStoreDirectory",
entity: "MallStore",
table: "StoreDirectory",
version: "1",
attributes: {
mallId: {
type: "string",
required: true,
},
storeId: {
type: "string",
required: true,
},
buildingId: {
type: "string",
required: true,
},
unitId: {
type: "string",
required: true,
},
category: {
type: [
"spite store",
"food/coffee",
"food/meal",
"clothing",
"electronics",
"department",
"misc"
],
required: true
},
leaseEndDate: {
type: "string",
required: true
},
rent: {
type: "string",
required: true,
validate: /^(\d+\.\d{2})$/
},
discount: {
type: "string",
required: false,
default: "0.00",
validate: /^(\d+\.\d{2})$/
}
},
indexes: {
stores: {
pk: {
field: "pk",
facets: ["storeId"]
},
sk: {
field: "sk",
facets: ["mallId", "buildingId", "unitId"]
}
},
malls: {
index: "idx1",
pk: {
field: "idx1pk",
facets: ["mallId"]
},
sk: {
field: "idx1sk",
facets: ["buildingId", "unitId", "storeId"]
}
},
leases: {
index: "idx2",
pk: {
field: "idx2pk",
facets: ["mallId"]
},
sk: {
field: "idx2pk",
facets: ["leaseEndDate", "storeId", "buildingId", "unitId"]
}
}
},
filters: {
byCategory: ({category}, name) => category.eq(name),
rentDiscount: (attributes, discount, max, min) => {
return `${attributes.discount.lte(discount)} AND ${attributes.rent.between(max, min)}`
}
}
};
Each record represents one Store location. All Stores are located in Malls we manage.
To satisfy requirements for searching based on location, you could use the following keys: Each MallStore record would have a Partition Key with the store's storeId. This key alone is not enough to identify a particular store. To solve this, compose a Sort Key for the store's location attribute ordered hierarchically (mall/building/unit): ["mallId", "buildingId", "unitId"].
The MallStore entity above, using just the stores Index alone enables four Access Patterns:
LatteLarrys locations in all MallsLatteLarrys locations in one MallLatteLarrys locations inside a specific MallLatteLarrys inside of a Mall and BuildingQueries in ElectroDB are built around the Access Patterns defined in the Schema and are capable of using partial key Facets to create performant lookups. To accomplish this, ElectroDB offers a predictable chainable API.
Examples in this section using the
MallStoreschema defined above.
The methods: Get (get), Create (put), Update (update), and Delete (delete) *require all facets described in the Entities' primary PK and SK.
Get MethodProvide all facets in an object to the get method
await StoreLocations.get({
storeId: "LatteLarrys",
mallId: "EastPointe",
buildingId: "BuildingA1",
unitId: "B47"
}).go();
Delete MethodProvide all facets in an object to the delete method to delete a record.
await StoreLocations.delete({
storeId: "LatteLarrys",
mallId: "EastPointe",
buildingId: "BuildingA1",
unitId: "B47"
}).go();
Put RecordProvide all required Attributes as defined in the model to create a new record. ElectroDB will enforce any defined validations, defaults, casting, and field aliasing.
let store = {
storeId: "LatteLarrys",
mallId: "EastPointe",
buildingId: "BuildingA1",
unitId: "B47",
category: "food/coffee",
leaseEndDate: "2020-03-22"
}
await StoreLocations.put(store).go();
Update RecordTo update a record, pass all facets to the update method and then pass set attributes that need to be updated.
Note: If your update includes changes to an attribute that is also a facet for a global secondary index, you must provide all facets for that index.
let storeId = "LatteLarrys";
let mallId = "EastPointe";
let buildingId = "BuildingA1";
let unitId = "B47";
let category = "food/meal";
await StoreLocations
.update({storeId, mallId, buildingId, unitId})
.set({category})
.go();
Scan RecordsWhen scanning for rows, you can use filters the same as you would any query. For more detial on filters, see the Filters section.
Note: Scan functionality will be scoped to your Entity. This means your results will only include records that match the Entity defined in the model.
await StoreLocations.scan
.filter(({category}) => `
${category.eq("food/coffee")} OR ${category.eq("spite store")}
`)
.filter(({leaseEndDate}) => `
${leaseEndDate.between("2020-03", "2020-04")}
`)
.go();
Query RecordsExamples in this section using the
MallStoreschema defined above.
All queries start from the Access Pattern defined in the schema.
const MallStore = new Entity(schema);
// Each Access Pattern is available on the Entity instance
// MallStore.query.stores()
// MallStore.query.malls()
All queries require (at minimum) the Facets included in its defined Partition Key. They can be supplied in the order they are composed or in a single object when invoking the Access Pattern.
const MallStore = new Entity(schema);
// stores
// pk: ["storeId"]
// sk: ["mallId", "buildingId", "unitId"]
let storeId = "LatteLarrys";
let mallId = "EastPointe";
// Good: As an object
MallStore.query.stores({storeId});
// Bad: Facets missing, will throw
MallStore.query.stores(); // err: Params passed to ENTITY method, must only include storeId
// Bad: Facets not included, will throw
MallStore.query.stores({mallId}); // err: Params passed to ENTITY method, must only include storeId
After invoking the Access Pattern with the required Partition Key Facets, you can now choose what Sort Key Facets are applicable to your query. Examine the table in Sort Key Operations for more information on the available operations on a Sort Key.
Collections allow you to query across Entities. To use them you need to join your Models onto a Service instance.
Using the TaskApp Models defined in Models, these models share a
collectioncalledassignmentson the indexgsi3pk-gsi3sk-index
let TaskApp = new Service({
version: "1",
service: "TaskApp",
table: "projectmanagement"
}, { client });
TaskApp.join(EmployeesModel); // TaskApp.entities.employees
TaskApp.join(TasksModel); // TaskApp.entities.tasks
Available on your Service are two objects: entites and collections. Entities available on entities have the same capabilities as they would if created individually. When a Model added to a Service with join however, its Collections are automatically added and validated with the other Models joined to that Service. These Collections are available on collections.
TaskApp.collections.assignments({employee: "JExotic"}).params();
// Results
{
TableName: 'projectmanagement',
ExpressionAttributeNames: { '#pk': 'gsi3pk', '#sk1': 'gsi3sk' },
ExpressionAttributeValues: { ':pk': '$taskapp_1#employee_joeexotic', ':sk1': '$assignments' },
KeyConditionExpression: '#pk = :pk and begins_with(#sk1, :sk1)',
IndexName: 'gsi3pk-gsi3sk-index'
}
Collections do not have the same query functionality and as an Entity, though it does allow for inline filters like an Entity. The attributes available on the filter object include all attributes across entities.
TaskApp.collections
.assignments({employee: "CBaskin"})
.filter((attributes) => `
${attributes.project.notExists()} OR ${attributes.project.contains("murder")}
`)
// Results
{
TableName: 'projectmanagement',
ExpressionAttributeNames: { '#project': 'project', '#pk': 'gsi3pk', '#sk1': 'gsi3sk' },
ExpressionAttributeValues: {
':project1': 'murder',
':pk': '$taskapp_1#employee_carolbaskin',
':sk1': '$assignments'
},
KeyConditionExpression: '#pk = :pk and begins_with(#sk1, :sk1)',
IndexName: 'gsi3pk-gsi3sk-index',
FilterExpression: '\n\t\tattribute_not_exists(#project) OR contains(#project, :project1)\n\t'
}
.go() and .params()Lastly, all query chains end with either a .go() or a .params() method invocation. These will either execute the query to DynamoDB (.go()) or return formatted parameters for use with the DynamoDB docClient (.params()).
Both .params() and .go() take a query configuration object which is detailed more in the section Query Options.
.params()The params method ends a query chain, and synchronously formats your query into an object ready for the DynamoDB docClient.
For more information on the options available in the
configobject, checkout the section Query Options.
let config = {};
let stores = MallStores.query
.leases({ mallId })
.between(
{ leaseEndDate: "2020-06-01" },
{ leaseEndDate: "2020-07-31" })
.filter(attr) => attr.rent.lte("5000.00"))
.params(config);
// Results:
{
IndexName: 'idx2',
TableName: 'electro',
ExpressionAttributeNames: { '#rent': 'rent', '#pk': 'idx2pk', '#sk1': 'idx2sk' },
ExpressionAttributeValues: {
':rent1': '5000.00',
':pk': '$mallstoredirectory_1#mallid_eastpointe',
':sk1': '$mallstore#leaseenddate_2020-06-01#rent_',
':sk2': '$mallstore#leaseenddate_2020-07-31#rent_'
},
KeyConditionExpression: '#pk = :pk and #sk1 BETWEEN :sk1 AND :sk2',
FilterExpression: '#rent <= :rent1'
}
.go()The go method ends a query chain, and asynchronously queries DynamoDB with the client provided in the model.
For more information on the options available in the
configobject, check out the section Query Options.
let config = {};
let stores = MallStores.query
.leases({ mallId })
.between(
{ leaseEndDate: "2020-06-01" },
{ leaseEndDate: "2020-07-31" })
.filter(({rent}) => rent.lte("5000.00"))
.go(config);
Below are all chain possibilities available, given the MallStore model.
// leases
// pk: ["mallId"]
// sk: ["buildingId", "unitId", "storeId"]
let mallId = "EastPointe";
// begins_with
MallStore.query.leases({mallId}).go()
MallStore.query.leases({mallId, leaseEndDate: "2020-03"}}).go();
MallStore.query.leases({mallId, leaseEndDate: "2020-03-22", rent: "2000.00"}).go();
// gt, gte, lt, lte
MallStore.query.leases({mallId}).gt({leaseEndDate}).go();
MallStore.query.leases({mallId}).gte({leaseEndDate}).go();
MallStore.query.leases({mallId}).lt({leaseEndDate}).go();
MallStore.query.leases({mallId}).lte({leaseEndDate}).go();
// between
MallStore.query.leases({mallId}).between({leaseEndDate: "2020-03"}, {leaseEndDate: "2020-04"}).go();
// filters -- applied after any of the sort key operators above
let june = "2020-06";
let july = "2020-07";
let discount = "500.00";
let maxRent = "2000.00";
let minRent = "5000.00";
MallStore.query
.leases({mallId, leaseEndDate: june})
.rentDiscount(discount, maxRent, minRent)
.go();
MallStore.query
.leases({mallId})
.between(
{leaseEndDate: june},
{leaseEndDate: july})
.byCategory("food/coffee")
.go();
By default ElectroDB enables you to work with records as the names and properties defined in the model. Additionally, it removes the need to deal directly with the docClient parameters which can be complex for a team without as much experience with DynamoDB. The Query Options object can be passed to both the .params() and .go() methods when building you query. Below are the options available:
let options = {
params: [object],
raw: [boolean],
includeKeys: [boolean],
originalErr: [boolean],
};
| Option | Description |
|---|---|
| params | Properties added to this object will be merged onto the params sent to the document client. Any conflicts with ElectroDB will favor the params specified here. |
| raw | Returns query results as they were returned by the docClient. |
| includeKeys | By default, ElectroDB does not return partition, sort, or global keys in its response. |
| originalErr | By default, ElectroDB alters the stacktrace of any exceptions thrown by the DynamoDB client to give better visibility to the developer. Set this value equal to true to turn off this functionality and return the error unchanged. |
For an example, lets look at the needs of application used to manage Employees. The application Looks at employees, offices, tasks, and projects.
const EmployeesModel = {
entity: "employees",
version: "1",
service: "taskapp",
table: "projectmanagement",
attributes: {
employee: {
type: "string",
},
firstName: {
type: "string",
},
lastName: {
type: "string",
},
office: {
type: "string",
},
title: {
type: "string",
},
team: {
type: ["development", "marketing", "finance", "product"],
},
salary: {
type: "string",
},
manager: {
type: "string",
},
dateHired: {
type: "string",
},
birthday: {
type: "string",
},
},
indexes: {
employee: {
pk: {
field: "pk",
facets: ["employee"],
},
sk: {
field: "sk",
facets: [],
},
},
coworkers: {
index: "gsi1pk-gsi1sk-index",
collection: "workplaces",
pk: {
field: "gsi1pk",
facets: ["office"],
},
sk: {
field: "gsi1sk",
facets: ["team", "title", "employee"],
},
},
teams: {
index: "gsi2pk-gsi2sk-index",
pk: {
field: "gsi2pk",
facets: ["team"],
},
sk: {
field: "gsi2sk",
facets: ["title", "salary", "employee"],
},
},
employeeLookup: {
collection: "assignements",
index: "gsi3pk-gsi3sk-index",
pk: {
field: "gsi3pk",
facets: ["employee"],
},
sk: {
field: "gsi3sk",
facets: [],
},
},
roles: {
index: "gsi4pk-gsi4sk-index",
pk: {
field: "gsi4pk",
facets: ["title"],
},
sk: {
field: "gsi4sk",
facets: ["salary", "employee"],
},
},
directReports: {
index: "gsi5pk-gsi5sk-index",
pk: {
field: "gsi5pk",
facets: ["manager"],
},
sk: {
field: "gsi5sk",
facets: ["team", "office", "employee"],
},
},
},
filters: {
upcomingCelebrations: (attributes, startDate, endDate) => {
let { dateHired, birthday } = attributes;
return `${dateHired.between(startDate, endDate)} OR ${birthday.between(
startDate,
endDate,
)}`;
},
},
};
const TasksModel = {
entity: "tasks",
version: "1",
service: "taskapp",
table: "projectmanagement",
attributes: {
task: {
type: "string",
},
project: {
type: "string",
},
employee: {
type: "string",
},
description: {
type: "string",
},
},
indexes: {
task: {
pk: {
field: "pk",
facets: ["task"],
},
sk: {
field: "sk",
facets: ["project", "employee"],
},
},
project: {
index: "gsi1pk-gsi1sk-index",
pk: {
field: "gsi1pk",
facets: ["project"],
},
sk: {
field: "gsi1sk",
facets: ["employee", "task"],
},
},
assigned: {
collection: "assignements",
index: "gsi3pk-gsi3sk-index",
pk: {
field: "gsi3pk",
facets: ["employee"],
},
sk: {
field: "gsi3sk",
facets: ["project", "task"],
},
},
},
};
const OfficesModel = {
entity: "offices",
version: "1",
table: "electro",
service: "electrotest",
attributes: {
office: {
type: "string",
},
country: {
type: "string",
},
state: {
type: "string",
},
city: {
type: "string",
},
zip: {
type: "string",
},
address: {
type: "string",
},
},
indexes: {
locations: {
pk: {
field: "pk",
facets: ["country", "state"],
},
sk: {
field: "sk",
facets: ["city", "zip", "office"],
},
},
office: {
index: "gsi1pk-gsi1sk-index",
collection: "workplaces",
pk: {
field: "gsi1pk",
facets: ["office"],
},
sk: {
field: "gsi1sk",
facets: [],
},
},
},
};
Join models on a new Service called EmployeeApp
const DynamoDB = require("aws-sdk/clients/dynamodb");
const client = new DynamoDB.DocumentClient({
region: "us-east-1",
});
const { Service } = require("electrodb");
let EmployeeApp = new Service(
{
version: "1",
service: "EmployeeApp",
table: "projectmanagement",
},
{ client },
);
EmployeeApp.join(EmployeesModel); // EmployeeApp.entities.employees
EmployeeApp.join(TasksModel); // EmployeeApp.entities.tasks
EmployeeApp.join(OfficesModel); // EmployeeApp.entities.tasks
Query RecordsEmployeeApp.collections.assignements({employee: "CBaskin"}).go();
Returns the following:
{
employees: [{
employee: "cbaskin",
firstName: "carol",
lastName: "baskin",
office: "big cat rescue",
title: "owner",
team: "cool cats and kittens",
salary: "1,000,000",
manager: "",
dateHired: "1992-11-04",
birthday: "1961-06-06",
}].
tasks: [{
task: "Feed tigers",
description: "Prepare food for tigers to eat",
project: "Keep tigers alive",
employee: "cbaskin"
}, {
task: "Fill water bowls",
description: "Ensure the tigers have enough water",
project: "Keep tigers alive",
employee: "cbaskin"
}]
}
EmployeeApp.collections.workplaces({office: "big cat rescue"}).go()
Returns the following:
{
employees: [{
employee: "cbaskin",
firstName: "carol",
lastName: "baskin",
office: "big cat rescue",
title: "owner",
team: "cool cats and kittens",
salary: "1,000,000",
manager: "",
dateHired: "1992-11-04",
birthday: "1961-06-06",
}],
offices: [{
office: "big cat rescue",
country: "usa",
state: "florida",
city: "tampa"
zip: "12345"
address: "123 Kitty Cat Lane"
}]
}
EmployeeApp.entities.tasks.query.assigned({employee: "cbaskin"}).go();
Returns the following:
[
{
task: "Feed tigers",
description: "Prepare food for tigers to eat",
project: "Keep tigers alive",
employee: "cbaskin"
}, {
task: "Fill water bowls",
description: "Ensure the tigers have enough water",
project: "Keep tigers alive",
employee: "cbaskin"
}
]
EmployeeApp.entities.tasks.query.project({project: "Murder Carol"}).go();
Returns the following:
[
{
task: "Hire hitman",
description: "Find someone to murder Carol",
project: "Murder Carol",
employee: "jexotic"
}
];
EmployeeApp.entities.office.locations({country: "usa", state: "florida"}).go()
Returns the following:
[
{
office: "big cat rescue",
country: "usa",
state: "florida",
city: "tampa"
zip: "12345"
address: "123 Kitty Cat Lane"
}
]
EmployeeApp.entities.employees
.roles({title: "animal wrangler"})
.lte({salary: "150.00"})
.go()
Returns the following:
[
{
employee: "ssaffery",
firstName: "saff",
lastName: "saffery",
office: "gw zoo",
title: "animal wrangler",
team: "keepers",
salary: "105.00",
manager: "jexotic",
dateHired: "1999-02-23",
birthday: "1960-07-11",
}
]
EmployeeApp.entities.employees
.workplaces({office: "gw zoo"})
.upcomingCelebrations("2020-05-01", "2020-06-01")
.go()
Returns the following:
[
{
employee: "jexotic",
firstName: "joe",
lastName: "maldonado-passage",
office: "gw zoo",
title: "tiger king",
team: "founders",
salary: "10000.00",
manager: "jlowe",
dateHired: "1999-02-23",
birthday: "1963-03-05",
}
]
EmployeeApp.entities.employees
.reports({manager: "jlowe"})
.go()
Returns the following:
[
{
employee: "jexotic",
firstName: "joe",
lastName: "maldonado-passage",
office: "gw zoo",
title: "tiger king",
team: "founders",
salary: "10000.00",
manager: "jlowe",
dateHired: "1999-02-23",
birthday: "1963-03-05",
}
]
For an example, lets look at the needs of application used to manage Shopping Mall properties. The application assists employees in the day-to-day operations of multiple Shopping Malls.
Create a new Entity using the MallStore schema defined above
const DynamoDB = require("aws-sdk/clients/dynamodb");
const client = new DynamoDB.DocumentClient();
const MallStore = new Entity(model, {client});
PUT Recordawait MallStore.create({
mallId: "EastPointe",
storeId: "LatteLarrys",
buildingId: "BuildingA1",
unitId: "B47",
category: "spite store",
leaseEndDate: "2020-02-29",
rent: "5000.00",
}).go();
Returns the following:
{
"mallId": "EastPointe",
"storeId": "LatteLarrys",
"buildingId": "BuildingA1",
"unitId": "B47",
"category": "spite store",
"leaseEndDate": "2020-02-29",
"rent": "5000.00",
"discount": "0.00",
}
UPDATE RecordWhen updating a record, you must include all Facets associated with the table's primary PK and SK.
let storeId = "LatteLarrys";
let mallId = "EastPointe";
let buildingId = "BuildingA1";
let unitId = "B47";
await StoreLocations.update({storeId, mallId, buildingId, unitId}).set({
leaseEndDate: "2021-02-28"
}).go();
Returns the following:
{
"leaseEndDate": "2021-02-28"
}
GET RecordWhen retrieving a specific record, you must include all Facets associated with the table's primary PK and SK.
let storeId = "LatteLarrys";
let mallId = "EastPointe";
let buildingId = "BuildingA1";
let unitId = "B47";
await StoreLocations.get({storeId, mallId, buildingId, unitId}).go();
Returns the following:
{
"mallId": "EastPointe",
"storeId": "LatteLarrys",
"buildingId": "BuildingA1",
"unitId": "B47",
"category": "spite store",
"leaseEndDate": "2021-02-28",
"rent": "5000.00",
"discount": "0.00"
}
DELETE RecordWhen removing a specific record, you must include all Facets associated with the table's primary PK and SK.
let storeId = "LatteLarrys";
let mallId = "EastPointe";
let buildingId = "BuildingA1";
let unitId = "B47";
let storeId = "LatteLarrys";
await StoreLocations.delete({storeId, mallId, buildingId, unitId}).go();
Returns the following:
{}
Query Records
let mallId = "EastPointe";
let stores = await StoreLocations.malls({mallId}).query().go();
let mallId = "EastPointe";
let buildingId = "BuildingA1";
let stores = await StoreLocations.malls({mallId}).query({buildingId}).go();
let mallId = "EastPointe";
let buildingId = "BuildingA1";
let unitId = "B47";
let stores = await StoreLocations.malls({mallId}).query({buildingId, unitId}).go();
let mallId = "EastPointe";
let category = "food/coffee";
let stores = await StoreLocations.malls({mallId}).byCategory(category).go();
let mallId = "EastPointe";
let q2StartDate = "2020-04-01";
let stores = await StoreLocations.leases({mallId}).lt({leaseEndDate: q2StateDate}).go();
let mallId = "EastPointe";
let q4StartDate = "2020-10-01";
let q4EndDate = "2020-12-31";
let stores = await StoreLocations.leases(mallId)
.between (
{leaseEndDate: q4StartDate},
{leaseEndDate: q4EndDate})
.go();
let mallId = "EastPointe";
let yearStarDate = "2020-01-01";
let yearEndDate = "2020-12-31";
let storeId = "LatteLarrys";
let stores = await StoreLocations.leases(mallId)
.between (
{leaseEndDate: yearStarDate},
{leaseEndDate: yearEndDate})
.filter(attr => attr.category.eq("Spite Store"))
.go();
let mallId = "EastPointe";
let buildingId = "BuildingA1";
let unitId = "B47";
let storeId = "LatteLarrys";
let stores = await StoreLocations.malls({mallId}).query({buildingId, storeId}).go();
.page() finish method (like .params() and .go()) to allow for easier pagination of resultslimit, pages, attributes, sort and more for easier querying.model to give more general control of interactions with the Entity.FAQs
A library to more easily create and interact with multiple entities and heretical relationships in dynamodb
The npm package electrodb receives a total of 411,753 weekly downloads. As such, electrodb popularity was classified as popular.
We found that electrodb demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 0 open source maintainers collaborating on the project.
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