DynamoBao
DynamoBao is a simple lightweight library for building DynamoDB models in JavaScript. I've used DynamoDB for years and generally love it, but find getting started difficult and repetitive. DynamoBao is the tool I wish I had when I started.
Principles
- Expose just enough of Dynamo's features to make it easy to model many common types of data.
- Don't break DynamoDB's superpower of infinite scale with consistent fast performance.
- Use single table design to minimize ops overhead, without adding complexity for the developer.
Key features
- Model 1:1, 1:N, N:M relationships between objects
- Efficiently load data: load related objects in parallel, cache data using loading contexts
- Minimize race conditions: save diffs, version checks on save, atomic counters
- Enforce unique constraints and use them for lookups
- Built-in multi-tenancy support with complete data isolation and concurrency safety
- Return total read/write consumed capacity (even when multiple operations were performed)
- Easily iterate over all items in a model for batch processing or migrations
- ESM (ECMAScript Modules) support for modern JavaScript projects
Requirements
- Node.js 12.17.0+ (for AsyncLocalStorage support in multi-tenant features)
- Node.js 14+ recommended for native ESM support
- AWS credentials configured for DynamoDB access
Example 1: Simple model
Step 1 is to define your models in a yaml file. Here's a simple example.
models:
User: {
modelPrefix: u
fields:
userId: {type: UlidField, autoAssign: true, required: true}
name: {type: StringField, required: true}
email: {type: EmailField, required: true}
primaryKey: {partitionKey: userId}
}
Based on this definition, the code generator will create a User
model in the models directory that you can use like this:
const { User } = require("./models/user");
const userConfig = require("./config");
const dynamoBao = require("dynamo-bao");
async function testUserModel() {
dynamoBao.initModels(userConfig);
// Create a new user
const user = new User({
name: "Test User",
email: "test@example.com",
});
await user.save();
console.log("Created user:", user);
console.log("Consumed capacity:", user.getNumericConsumedCapacity());
}
testUserModel();
Example 2: Relationships and unique constraints
models:
User:
modelPrefix: u # required short string to identify the model
fields:
userId: {type: UlidField, autoAssign: true, required: true}
name: {type: StringField, required: true}
email: {type: EmailField, required: true}
primaryKey: {partitionKey: userId} # required
# Add up to 3 unique constraints each with a unique id: uc1, uc2, uc3
uniqueConstraints: {uniqueEmail: {field: email, uniqueConstraintId: uc1}}
Post:
modelPrefix: p
fields:
postId: {type: UlidField, autoAssign: true}
# Enables getUser on a Post object / load related data
userId: {type: RelatedField, model: User, required: true}
title: {type: StringField, required: true}
content: {type: StringField, required: true}
primaryKey: {partitionKey: postId}
indexes:
# Add up to 3 indexes; make sure each index has a unique id: gsi1, gsi2, gsi3
# Enables user.queryPosts() to query posts for a user
postsForUser: {partitionKey: userId, sortKey: postId, indexId: gsi2}
const { User } = require("./models/user");
const { Post } = require("./models/post");
const userConfig = require("./config");
const dynamoBao = require("dynamo-bao");
async function testUserModel() {
dynamoBao.initModels(userConfig);
// Create a new user
const user = new User({
name: "Test User",
email: "test@example.com",
});
await user.save();
console.log("Created user:", user.userId);
// Find user by unique constraint
const foundUser = await User.findByEmail("test@example.com");
console.log("Found user by email:", foundUser);
// Create some test posts for the user
const post1 = new Post({
userId: user.userId,
title: "Test Post 1",
content: "This is a test post",
});
const post2 = new Post({
userId: user.userId,
title: "Test Post 2",
content: "This is another test post",
});
await Promise.all([post1.save(), post2.save()]);
// User now has a queryPosts method (via the postsForUser index)
const userPosts = await user.queryPosts();
console.log("User posts:", userPosts.items.length);
// Or add a filter condition to the query
const filteredPosts = await user.queryPosts(null, {
filter: {
content: {
$contains: "another"
}
}
});
console.log("User posts matching filter:", filteredPosts.items.length);
}
testUserModel();
Cloudflare Workers Support
DynamoBao supports Cloudflare Workers with request-scoped batching to ensure proper isolation between concurrent requests. To use DynamoBao in Cloudflare Workers, you'll need to enable Node.js compatibility and wrap your request handlers with the batch context:
// wrangler.toml
compatibility_flags = ["nodejs_compat"];
compatibility_date = "2024-09-23";
// worker.js
import { runWithBatchContext } from "dynamo-bao";
import { User } from "./models/user.js";
export default {
async fetch(request, env, ctx) {
return runWithBatchContext(async () => {
// All batching operations are now request-scoped
const user = await User.find(userId);
// Additional database operations...
return new Response(JSON.stringify(user));
});
},
};
Request Isolation:
- With
runWithBatchContext
: Each request gets its own isolated batch context with optimal batching performance - Without
runWithBatchContext
: Operations automatically fall back to direct execution (no batching/caching) to ensure request isolation
For production Cloudflare Workers deployments, always use runWithBatchContext
to get both safety and optimal performance.
Batch Context Configuration
DynamoBao provides flexible batch context behavior that can be configured based on your application's needs:
Configuration Options
Add the batchContext
configuration to your config file:
// config.js or dynamo-bao.config.js
module.exports = {
aws: {
region: "us-west-2",
},
db: {
tableName: "your-table-name",
},
batchContext: {
requireBatchContext: false, // Default: allow fallback behavior
},
// ... other config
};
Behavior Modes
Default Mode (requireBatchContext: false
):
- Operations inside
runWithBatchContext
: Full batching and caching enabled - Operations outside
runWithBatchContext
: Direct execution without batching or caching - Provides maximum flexibility and backward compatibility
// Works with direct execution (no batching/caching)
const user = await User.find("user123");
// Also works with batching + caching
await runWithBatchContext(async () => {
const user = await User.find("user123");
});
Strict Mode (requireBatchContext: true
):
- Operations inside
runWithBatchContext
: Full batching and caching enabled - Operations outside
runWithBatchContext
: Throws an error - Ensures all database operations use proper batch context
// Configure strict mode
const manager = initModels({
batchContext: { requireBatchContext: true },
});
// This throws an error
await User.find("user123"); // Error: Batch operations must be executed within runWithBatchContext()
// This works
await runWithBatchContext(async () => {
const user = await User.find("user123"); // ✅
});
Context Detection API
You can check if code is currently running within a batch context:
const { User } = require("./models/user");
// Check if inside batch context
const isInBatchContext = User.isInsideBatchContext();
if (isInBatchContext) {
// Full batching and caching available
console.log("Running with batching enabled");
} else {
// Direct execution mode
console.log("Running in direct execution mode");
}
Environment Variable Support
You can also configure batch context behavior via environment variables:
# Enable strict mode globally
export DYNAMO_BAO_REQUIRE_BATCH_CONTEXT=true
# Your application will now require runWithBatchContext for all operations
node your-app.js
This is particularly useful for:
- Development/Testing: Use strict mode to catch missing batch contexts early
- Production: Use default mode for maximum flexibility
- Migration: Gradually migrate from direct calls to batch context usage
Iterating over all items
DynamoBao makes it easy to iterate over all items in a model, which is useful for tasks like data migration, backfills, or reporting.
By default, all models are created with iterable: true
. This automatically sets up a dedicated index that allows you to use the iterateAll()
method on the model class.
// Iterate over all posts, 100 at a time
for await (const batch of Post.iterateAll({ batchSize: 100 })) {
for (const post of batch) {
console.log(post.title);
}
}
Cost and Performance
This convenience comes at a cost: every create
, update
, or delete
operation on an iterable model requires a second write to the database to maintain the iteration index. This doubles the write cost for every item.
To prevent "hot partitions" on large models, the iteration index is automatically split into 10 "buckets" or partitions. The iterateAll()
method handles fetching from all buckets seamlessly.
Opting Out
For high-volume, write-heavy models where you know you will never need to iterate (e.g., logging tables), you can disable this feature to save costs:
models:
AnalyticsEvent:
modelPrefix: "ae"
iterable: false # Disabling iteration for this write-heavy model
fields:
# ...
Installation / Quick Start
Make sure you have AWS credentials setup in your environment. You'll also need node and npm installed.
Create a project and setup some models. You'll also need to install DynamoBao locally in your project.
mkdir your-project
cd your-project
npm install dynamo-bao
Create a new Dynamo table for your project. You should have one table per project.
npx bao-init
This creates a config.js
which contains settings for your project like AWS region and the table name.
It also creates a models.yaml
file with a simple example model, and a models
directory where the generated models will be stored.
Edit your models.yaml
file to define these models.
models:
User:
modelPrefix: u # required short string to identify the model
fields:
userId: { type: UlidField, autoAssign: true, required: true }
name: { type: StringField, required: true }
email: { type: StringField, required: true }
profilePictureUrl: { type: StringField }
createdAt: { type: CreateDateField }
modifiedAt: { type: ModifiedDateField }
role: { type: StringField }
primaryKey:
partitionKey: userId
uniqueConstraints:
# Enforces unique constraint on email field and enables User.findByEmail()
uniqueEmail: { field: email, uniqueConstraintId: uc1 }
Post:
modelPrefix: p # required short string to identify the model
fields:
postId: { type: UlidField, autoAssign: true }
userId: { type: RelatedField, model: User, required: true }
title: { type: StringField, required: true }
content: { type: StringField, required: true }
createdAt: { type: CreateDateField }
version: { type: VersionField }
primaryKey:
partitionKey: postId
indexes:
# Enables user.queryPosts() to query posts for a user
postsForUser: { partitionKey: userId, sortKey: createdAt, indexId: gsi2 }
Run the code generator to create the models. You can also run npx bao-watch
to automatically regenerate the models when you make changes.
npx bao-codegen
You should now have generated models in the models
directory.
ESM Support
DynamoBao supports generating models as ESM (ECMAScript Modules) for modern JavaScript projects. To enable ESM code generation, add the codegen
configuration to your config.js
:
// config.js
module.exports = {
aws: {
region: "us-west-2",
},
db: {
tableName: "your-table-name",
},
codegen: {
moduleSystem: "esm", // Options: 'commonjs' (default) or 'esm'
},
// ... other config
};
When ESM is enabled, generated models will use:
import
/export
syntax instead ofrequire
/module.exports
.js
extensions in import paths for ESM compatibility
For ESM config files, you can use .mjs
extension:
// dynamo-bao.config.mjs
export default {
codegen: {
moduleSystem: "esm",
},
// ... other config
};
Then use the generated ESM models:
// With ESM enabled
import { User } from "./models/user.js";
import { Post } from "./models/post.js";
Let's try using the models. Add the following code to a file called example.js
.
// example.js
const { User } = require("./models/user");
const { Post } = require("./models/post");
const userConfig = require("./config");
const dynamoBao = require("dynamo-bao");
async function testUserModel() {
dynamoBao.initModels(userConfig);
// Find user by email
const existingUser = await User.findByEmail("test@example.com");
console.log("Found user by email:", existingUser.exists());
if (existingUser.exists()) {
await User.delete(existingUser.getPrimaryId());
console.log("Deleted existing user");
await new Promise((resolve) => setTimeout(resolve, 100)); // 100ms
}
// Create a new user
const user = new User({
name: "Test User",
email: "test@example.com",
role: "user",
profilePictureUrl: "https://example.com/profile.jpg",
});
await user.save();
console.log("Created user:", user.getPrimaryId());
// Find user by email
const foundUser = await User.findByEmail("test@example.com");
console.log("Found user by email:", foundUser.getPrimaryId());
// Create some test posts for the user
const post1 = new Post({
userId: user.userId,
title: "Test Post 1",
content: "This is a test post",
});
const post2 = new Post({
userId: user.userId,
title: "Test Post 2",
content: "This is another test post",
});
await Promise.all([post1.save(), post2.save()]);
// Query user posts
const userPosts = await user.queryPosts();
console.log("User posts:", userPosts.items.length);
// Or add a filter condition to the query
const filteredPosts = await user.queryPosts(null, {
filter: { content: { $contains: "another" } },
});
console.log("User posts matching filter:", filteredPosts.items.length);
}
// Run the test
testUserModel();
Run the example.
node example.js
You should see something similar to this:
% node example.js
Found user by email: false
Created user: 01JFGMRH7XACZ8GKB81DZ5YWNH
Found user by email: 01JFGMRH7XACZ8GKB81DZ5YWNH
User posts: 2
User posts matching filter: 1
Congratulations! You're now harnessing the power of DynamoDB.
It's worth noting that you didn't have to:
- Configure or create a new table when adding a new model
- Install a database (either locally or on a server)
- Understand how to generate keys and indexes using single table design princples
- Manually configure transactions and items to support unique constraints