vogels

DynamoDB data mapper

vogels

vogels is a DynamoDB data mapper for node.js.

Features

Simplified data modeling and mapping to DynamoDB types
Advanced chainable apis for query and scan operations
Data validation
Autogenerating UUIDs
Global Secondary Indexes
Local Secondary Indexes
Parallel Scans

Installation

npm install vogels

Getting Started

First, you need to configure the AWS SDK with your credentials.

var vogels = require('vogels');
vogels.AWS.config.loadFromPath('credentials.json');

When running on EC2 its recommended to leverage EC2 IAM roles. If you have configured your instance to use IAM roles, Vogels will automatically select these credentials for use in your application, and you do not need to manually provide credentials in any other format.

var vogels = require('vogels');
vogels.AWS.config.update({region: "REGION"}); // region must be set

You can also directly pass in your access key id, secret and region.

Its recommend you not hard-code credentials inside an application. Use this method only for small personal scripts or for testing purposes.

var vogels = require('vogels');
vogels.AWS.config.update({accessKeyId: 'AKID', secretAccessKey: 'SECRET', region: "REGION"});

Currently the following region codes are available in Amazon:

Code	Name
ap-northeast-1	Asia Pacific (Tokyo)
ap-southeast-1	Asia Pacific (Singapore)
ap-southeast-2	Asia Pacific (Sydney)
eu-central-1	EU (Frankfurt)
eu-west-1	EU (Ireland)
sa-east-1	South America (Sao Paulo)
us-east-1	US East (N. Virginia)
us-west-1	US West (N. California)
us-west-2	US West (Oregon)

Define a Model

Models are defined through the toplevel define method.

var Account = vogels.define('Account', {
  hashKey : 'email',
 
  // add the timestamp attributes (updatedAt, createdAt) 
  timestamps : true,
 
  schema : {
    email   : Joi.string().email(),
    name    : Joi.string(),
    age     : Joi.number(),
    roles   : vogels.types.stringSet(),
    settings : {
      nickname      : Joi.string(),
      acceptedTerms : Joi.boolean().default(false)
    }
  }
});

Models can also be defined with hash and range keys.

var BlogPost = vogels.define('BlogPost', {
  hashKey : 'email',
  rangeKey : ‘title’,
  schema : {
    email   : Joi.string().email(),
    title   : Joi.string(),
    content : Joi.binary(),
    tags   : vogels.types.stringSet(),
  }
});

Schema Types

Vogels provides the following schema types:

String
Number
StringSet
NumberSet
Boolean
Date
UUID
TimeUUID

UUID

UUIDs can be declared for any attributes, including hash and range keys. By Default, the uuid will be automatically generated when attempting to create the model in DynamoDB.

var Tweet = vogels.define('Tweet', {
  hashKey : 'TweetID',
  timestamps : true,
  schema : {
    TweetID : vogels.types.uuid(),
    content : Joi.string(),
  }
});

Configuration

You can configure vogels to automatically add createdAt and updatedAt timestamp attributes when saving and updating a model. updatedAt will only be set when updating a record and will not be set on initial creation of the model.

var Account = vogels.define('Account', {
  hashKey : 'email',
 
  // add the timestamp attributes (updatedAt, createdAt) 
  timestamps : true,
 
  schema : {
    email : Joi.string().email(),
  }
});

If you want vogels to handle timestamps, but only want some of them, or want your timestamps to be called something else, you can override each attribute individually:

var Account = vogels.define('Account', {
  hashKey : 'email',
 
  // enable timestamps support 
  timestamps : true,
 
  // I don't want createdAt 
  createdAt: false,
 
  // I want updatedAt to actually be called updateTimestamp 
  updatedAt: 'updateTimestamp'
 
  schema : {
    email : Joi.string().email(),
  }
});

You can override the table name the model will use.

var Event = vogels.define('Event', {
  hashKey : 'name',
  schema : {
    name : Joi.string(),
    total : Joi.number()
  },
 
  tableName: 'deviceEvents'
});

if you set the tableName to a function, vogels will use the result of the function as the active table to use. Useful for storing time series data.

var Event = vogels.define('Event', {
  hashKey : 'name',
  schema : {
    name : Joi.string(),
    total : Joi.number()
  },
 
  // store monthly event data 
  tableName: function () {
    var d = new Date();
    return ['events', d.getFullYear(), d.getMonth() + 1].join('_');
  }
});

After you've defined your model you can configure the table name to use. By default, the table name used will be the lowercased and pluralized version of the name you provided when defining the model.

Account.config({tableName: 'AccountsTable'});

You can also pass in a custom instance of the aws-sdk DynamoDB client

var dynamodb = new AWS.DynamoDB();
Account.config({dynamodb: dynamodb});
 
// or globally use custom DynamoDB instance 
// all defined models will now use this driver 
vogels.dynamoDriver(dynamodb);

Saving Models to DynamoDB

With your models defined, we can start saving them to DynamoDB.

Account.create({email: 'foo@example.com', name: 'Foo Bar', age: 21}, function (err, acc) {
  console.log('created account in DynamoDB', acc.get('email'));
});

You can also first instantiate a model and then save it.

var acc = new Account({email: 'test@example.com', name: 'Test Example'});
acc.save(function (err) {
  console.log('created account in DynamoDB', acc.get('email'));
});

Saving models that require range and hashkeys are identical to ones with only hashkeys.

BlogPost.create({
  email: 'werner@example.com', 
  title: 'Expanding the Cloud', 
  content: 'Today, we are excited to announce the limited preview...'
  }, function (err, post) {
    console.log('created blog post', post.get('title'));
  });

Pass an array of items and they will be saved in parallel to DynamoDB.

var item1 = {email: 'foo1@example.com', name: 'Foo 1', age: 10};
var item2 = {email: 'foo2@example.com', name: 'Foo 2', age: 20};
var item3 = {email: 'foo3@example.com', name: 'Foo 3', age: 30};
 
Account.create([item1, item2, item3], function (err, acccounts) {
  console.log('created 3 accounts in DynamoDB', accounts);
});

Use expressions api to do conditional writes

  var params = {};
  params.ConditionExpression = '#i <> :x';
  params.ExpressionAttributeNames = {'#i' : 'id'};
  params.ExpressionAttributeValues = {':x' : 123};
 
  User.create({id : 123, name : 'Kurt Warner' }, params, function (error, acc) { ... });

Use the overwrite option to prevent over writing of existing records.

By default overwrite is set to true, allowing create operations to overwrite existing records

  // setting overwrite to false will generate 
  // the same Condition Expression as in the previous example 
  User.create({id : 123, name : 'Kurt Warner' }, {overwrite : false}, function (error, acc) { ... });

Updating

When updating a model the hash and range key attributes must be given, all other attributes are optional

// update the name of the foo@example.com account 
Account.update({email: 'foo@example.com', name: 'Bar Tester'}, function (err, acc) {
  console.log('update account', acc.get('name'));
});

Model.update accepts options to pass to DynamoDB when making the updateItem request

Account.update({email: 'foo@example.com', name: 'Bar Tester'}, {ReturnValues: 'ALL_OLD'}, function (err, acc) {
  console.log('update account', acc.get('name')); // prints the old account name 
});
 
// Only update the account if the current age of the account is 21 
Account.update({email: 'foo@example.com', name: 'Bar Tester'}, {expected: {age: 22}}, function (err, acc) {
  console.log('update account', acc.get('name'));
});
 
// setting an attribute to null will delete the attribute from DynamoDB 
Account.update({email: 'foo@example.com', age: null}, function (err, acc) {
  console.log('update account', acc.get('age')); // prints null 
});

You can also pass what action to perform when updating a given attribute Use $add to increment or decrement numbers and add values to sets

Account.update({email : 'foo@example.com', age : {$add : 1}}, function (err, acc) {
  console.log('incremented age by 1', acc.get('age'));
});
 
BlogPost.update({
  email : 'werner@example.com',
  title : 'Expanding the Cloud',
  tags  : {$add : 'cloud'}
}, function (err, post) {
  console.log('added single tag to blog post', post.get('tags'));
});
 
BlogPost.update({
  email : 'werner@example.com',
  title : 'Expanding the Cloud',
  tags  : {$add : ['cloud', 'dynamodb']}
}, function (err, post) {
  console.log('added tags to blog post', post.get('tags'));
});

$del will remove values from a given set

BlogPost.update({
  email : 'werner@example.com',
  title : 'Expanding the Cloud',
  tags  : {$del : 'cloud'}
}, function (err, post) {
  console.log('removed cloud tag from blog post', post.get('tags'));
});
 
BlogPost.update({
  email : 'werner@example.com',
  title : 'Expanding the Cloud',
  tags  : {$del : ['aws', 'node']}
}, function (err, post) {
  console.log('removed multiple tags', post.get('tags'));
});

Use the expressions api to update nested documents

var params = {};
  params.UpdateExpression = 'SET #year = #year + :inc, #dir.titles = list_append(#dir.titles, :title), #act[0].firstName = :firstName ADD tags :tag';
  params.ConditionExpression = '#year = :current';
  params.ExpressionAttributeNames = {
    '#year' : 'releaseYear',
    '#dir' : 'director',
    '#act' : 'actors'
  };
 
  params.ExpressionAttributeValues = {
    ':inc' : 1,
    ':current' : 2001,
    ':title' : ['The Man'],
    ':firstName' : 'Rob',
    ':tag' : vogels.Set(['Sports', 'Horror'], 'S')
  };
 
Movie.update({title : 'Movie 0', description : 'This is a description'}, params, function (err, mov) {});

Deleting

You delete items in DynamoDB using the hashkey of model If your model uses both a hash and range key, than both need to be provided

Account.destroy('foo@example.com', function (err) {
  console.log('account deleted');
});
 
// Destroy model using hash and range key 
BlogPost.destroy('foo@example.com', 'Hello World!', function (err) {
  console.log('post deleted')
});
 
BlogPost.destroy({email: 'foo@example.com', title: 'Another Post'}, function (err) {
  console.log('another post deleted')
});

Model.destroy accepts options to pass to DynamoDB when making the deleteItem request

Account.destroy('foo@example.com', {ReturnValues: true}, function (err, acc) {
  console.log('account deleted');
  console.log('deleted account name', acc.get('name'));
});
 
Account.destroy('foo@example.com', {expected: {age: 22}}, function (err) {
  console.log('account deleted if the age was 22');

Use expression apis to perform conditional deletes

var params = {};
params.ConditionExpression = '#v = :x';
params.ExpressionAttributeNames = {'#v' : 'version'};
params.ExpressionAttributeValues = {':x' : '2'};
 
User.destroy({id : 123}, params, function (err, acc) {});

Loading models from DynamoDB

The simpliest way to get an item from DynamoDB is by hashkey.

Account.get('test@example.com', function (err, acc) {
  console.log('got account', acc.get('email'));
});

Perform the same get request, but this time peform a consistent read.

Account.get('test@example.com', {ConsistentRead: true}, function (err, acc) {
  console.log('got account', acc.get('email'));
});

Model.get accepts any options that DynamoDB getItem request supports. For example:

Account.get('test@example.com', {ConsistentRead: true, AttributesToGet : ['name','age']}, function (err, acc) {
  console.log('got account', acc.get('email'))
  console.log(acc.get('name'));
  console.log(acc.get('age'));
  console.log(acc.get('email')); // prints null 
});

Get a model using hash and range key.

// load up blog post written by Werner, titled DynamoDB Keeps Getting Better and cheaper 
BlogPost.get('werner@example.com', 'dynamodb-keeps-getting-better-and-cheaper', function (err, post) {
  console.log('loaded post by range and hash key', post.get('content'));
});

Model.get also supports passing an object which contains hash and range key attributes to load up a model

BlogPost.get({email: 'werner@example.com', title: 'Expanding the Cloud'}, function (err, post) {
  console.log('loded post', post.get('content'));
});

Use expressions api to select which attributes you want returned

  User.get({ id : '123456789'},{ ProjectionExpression : 'email, age, settings.nickname' }, function (err, acc) {});

Query

For models that use hash and range keys Vogels provides a flexible and chainable query api

// query for blog posts by werner@example.com 
BlogPost
  .query('werner@example.com')
  .exec(callback);
 
// same as above, but load all results 
BlogPost
  .query('werner@example.com')
  .loadAll()
  .exec(callback);
 
// only load the first 5 posts by werner 
BlogPost
  .query('werner@example.com')
  .limit(5)
  .exec(callback);
 
// query for posts by werner where the tile begins with 'Expanding' 
BlogPost
  .query('werner@example.com')
  .where('title').beginsWith('Expanding')
  .exec(callback);
 
// return only the count of documents that begin with the title Expanding 
BlogPost
  .query('werner@example.com')
  .where('title').beginsWith('Expanding')
  .select('COUNT')
  .exec(callback);
 
// only return title and content attributes of 10 blog posts 
// that begin with the title Expanding 
BlogPost
  .query('werner@example.com')
  .where('title').beginsWith('Expanding')
  .attributes(['title', 'content'])
  .limit(10)
  .exec(callback);
 
// sorting by title ascending 
BlogPost
  .query('werner@example.com')
  .ascending()
  .exec(callback)
 
// sorting by title descending 
BlogPost
  .query('werner@example.com')
  .descending()
  .exec(callback)
 
// All query options are chainable 
BlogPost
  .query('werner@example.com')
  .where('title').gt('Expanding')
  .attributes(['title', 'content'])
  .limit(10)
  .ascending()
  .loadAll()
  .exec(callback);

Vogels supports all the possible KeyConditions that DynamoDB currently supports.

BlogPost
  .query('werner@example.com')
  .where('title').equals('Expanding')
  .exec();
 
// less than equals 
BlogPost
  .query('werner@example.com')
  .where('title').lte('Expanding')
  .exec();
 
// less than 
BlogPost
  .query('werner@example.com')
  .where('title').lt('Expanding')
  .exec();
 
// greater than 
BlogPost
  .query('werner@example.com')
  .where('title').gt('Expanding')
  .exec();
 
// greater than equals 
BlogPost
  .query('werner@example.com')
  .where('title').gte('Expanding')
  .exec();
 
BlogPost
  .query('werner@example.com')
  .where('title').beginsWith('Expanding')
  .exec();
 
BlogPost
  .query('werner@example.com')
  .where('title').between('foo@example.com', 'test@example.com')
  .exec();

Query Filters allow you to further filter results on non-key attributes.

BlogPost
  .query('werner@example.com')
  .where('title').equals('Expanding')
  .filter('tags').contains('cloud')
  .exec();

Expression Filters also allow you to further filter results on non-key attributes.

BlogPost
  .query('werner@example.com')
  .filterExpression('#title < :t')
  .expressionAttributeValues({ ':t' : 'Expanding' })
  .expressionAttributeNames({ '#title' : 'title'})
  .projectionExpression('#title, tag')
  .exec();

See the queryFilter.js example for more examples of using query filters

Global Indexes

First, define a model with a global secondary index.

var GameScore = vogels.define('GameScore', {
  hashKey : 'userId',
  rangeKey : 'gameTitle',
  schema : {
    userId           : Joi.string(),
    gameTitle        : Joi.string(),
    topScore         : Joi.number(),
    topScoreDateTime : Joi.date(),
    wins             : Joi.number(),
    losses           : Joi.number()
  },
  indexes : [{
    hashKey : 'gameTitle', rangeKey : 'topScore', name : 'GameTitleIndex', type : 'global'
  }]
});

Now we can query against the global index

GameScore
  .query('Galaxy Invaders')
  .usingIndex('GameTitleIndex')
  .descending()
  .exec(callback);

When can also configure the attributes projected into the index. By default all attributes will be projected when no Projection pramater is present

var GameScore = vogels.define('GameScore', {
  hashKey : 'userId',
  rangeKey : 'gameTitle',
  schema : {
    userId           : Joi.string(),
    gameTitle        : Joi.string(),
    topScore         : Joi.number(),
    topScoreDateTime : Joi.date(),
    wins             : Joi.number(),
    losses           : Joi.number()
  },
  indexes : [{
    hashKey : 'gameTitle',
    rangeKey : 'topScore',
    name : 'GameTitleIndex',
    type : 'global',
    projection: { NonKeyAttributes: [ 'wins' ], ProjectionType: 'INCLUDE' } //optional, defaults to ALL 
 
  }]
});

Filter items against the configured rangekey for the global index.

GameScore
  .query('Galaxy Invaders')
  .usingIndex('GameTitleIndex')
  .where('topScore').gt(1000)
  .descending()
  .exec(function (err, data) {
    console.log(_.map(data.Items, JSON.stringify));
  });

Local Secondary Indexes

First, define a model using a local secondary index

var BlogPost = vogels.define('Account', {
  hashKey : 'email',
  rangekey : 'title',
  schema : {
    email             : Joi.string().email(),
    title             : Joi.string(),
    content           : Joi.binary(),
    PublishedDateTime : Joi.date()
  },
 
  indexes : [{
    hashkey : 'email', rangekey : 'PublishedDateTime', type : 'local', name : 'PublishedIndex'
  }]
});

Now we can query for blog posts using the secondary index

BlogPost
  .query('werner@example.com')
  .usingIndex('PublishedIndex')
  .descending()
  .exec(callback);

Could also query for published posts, but this time return oldest first

BlogPost
  .query('werner@example.com')
  .usingIndex('PublishedIndex')
  .ascending()
  .exec(callback);

Finally lets load all published posts sorted by publish date

BlogPost
  .query('werner@example.com')
  .usingIndex('PublishedIndex')
  .descending()
  .loadAll()
  .exec(callback);

Learn more about secondary indexes

Scan

Vogels provides a flexible and chainable api for scanning over all your items This api is very similar to the query api.

// scan all accounts, returning the first page or results 
Account.scan().exec(callback);
 
// scan all accounts, this time loading all results 
// note this will potentially make several calls to DynamoDB  
// in order to load all results 
Account
  .scan()
  .loadAll()
  .exec(callback);
 
// Load 20 accounts 
Account
  .scan()
  .limit(20)
  .exec();
 
// Load All accounts, 20 at a time per request 
Account
  .scan()
  .limit(20)
  .loadAll()
  .exec();
 
// Load accounts which match a filter 
// only return email and created attributes 
// and return back the consumed capacity the request took 
Account
  .scan()
  .where('email').gte('f@example.com')
  .attributes(['email','created'])
  .returnConsumedCapacity()
  .exec();
 
// Returns number of matching accounts, rather than the matching accounts themselves 
Account
  .scan()
  .where('age').gte(21)
  .select('COUNT')
  .exec();
 
// Start scan using start key 
Account
  .scan()
  .where('age').notNull()
  .startKey('foo@example.com')
  .exec()

Vogels supports all the possible Scan Filters that DynamoDB currently supports.

// equals 
Account
  .scan()
  .where('name').equals('Werner')
  .exec();
 
// not equals 
Account
  .scan()
  .where('name').ne('Werner')
  .exec();
 
// less than equals 
Account
  .scan()
  .where('name').lte('Werner')
  .exec();
 
// less than 
Account
  .scan()
  .where('name').lt('Werner')
  .exec();
 
// greater than equals 
Account
  .scan()
  .where('name').gte('Werner')
  .exec();
 
// greater than 
Account
  .scan()
  .where('name').gt('Werner')
  .exec();
 
// name attribute doesn't exist 
Account
  .scan()
  .where('name').null()
  .exec();
 
// name attribute exists 
Account
  .scan()
  .where('name').notNull()
  .exec();
 
// contains 
Account
  .scan()
  .where('name').contains('ner')
  .exec();
 
// not contains 
Account
  .scan()
  .where('name').notContains('ner')
  .exec();
 
// in 
Account
  .scan()
  .where('name').in(['foo@example.com', 'bar@example.com'])
  .exec();
 
// begins with 
Account
  .scan()
  .where('name').beginsWith('Werner')
  .exec();
 
// between 
Account
  .scan()
  .where('name').between('Bar', 'Foo')
  .exec();
 
// multiple filters 
Account
  .scan()
  .where('name').equals('Werner')
  .where('age').notNull()
  .exec();

You can also use the new expressions api when filtering scans

User.scan()
  .filterExpression('#age BETWEEN :low AND :high AND begins_with(#email, :e)')
  .expressionAttributeValues({ ':low' : 18, ':high' : 22, ':e' : 'test1'})
  .expressionAttributeNames({ '#age' : 'age', '#email' : 'email'})
  .projectionExpression('#age, #email')
  .exec();

Parallel Scan

Parallel scans increase the throughput of your table scans. The parallel scan operation is identical to the scan api. The only difference is you must provide the total number of segments

Caution you can easily consume all your provisioned throughput with this api

var totalSegments = 8;
 
Account.parallelScan(totalSegments)
  .where('age').gte(18)
  .attributes('age')
  .exec(callback);
 
// Load All accounts 
Account
  .parallelScan(totalSegments)
  .exec()

More info on Parallel Scans

Batch Get Items

Model.getItems allows you to load multiple models with a single request to DynamoDB.

DynamoDB limits the number of items you can get to 100 or 1MB of data for a single request. Vogels automatically handles splitting up into multiple requests to load all items.

Account.getItems(['foo@example.com','bar@example.com', 'test@example.com'], function (err, accounts) {
  console.log('loaded ' + accounts.length + ' accounts'); // prints loaded 3 accounts 
});
 
// For models with range keys you must pass in objects of hash and range key attributes 
var postKey1 = {email : 'test@example.com', title : 'Hello World!'};
var postKey2 = {email : 'test@example.com', title : 'Another Post'};
 
BlogPost.getItems([postKey1, postKey2], function (err, posts) {
  console.log('loaded posts');
});

Model.getItems accepts options which will be passed to DynamoDB when making the batchGetItem request

// Get both accounts, using a consistent read 
Account.getItems(['foo@example.com','bar@example.com'], {ConsistentRead: true}, function (err, accounts) {
  console.log('loaded ' + accounts.length + ' accounts'); // prints loaded 2 accounts 
});

Streaming api

vogels supports a basic streaming api in addition to the callback api for query, scan, and parallelScan operations.

var stream = Account.parallelScan(4).exec();
 
stream.on('readable', function () {
  console.log('single parallel scan response', stream.read());
});
 
stream.on('end', function () {
  console.log('Parallel scan of accounts finished');
});
 
var querystream = BlogPost.query('werner@vogels.com').loadAll().exec();
 
querystream.on('readable', function () {
  console.log('single query response', stream.read());
});
 
querystream.on('end', function () {
  console.log('query for blog posts finished');
});

Dynamic Table Names

vogels supports dynamic table names, useful for storing time series data.

var Event = vogels.define('Event', {
  hashKey : 'name',
  schema : {
    name : Joi.string(),
    total : Joi.number()
  },
 
  // store monthly event data 
  tableName: function () {
    var d = new Date();
    return ['events', d.getFullYear(), d.getMonth() + 1].join('_');
  }
});

Logging

Logging can be enabled to provide detailed information on data being sent and returned from DynamoDB. By default logging is turned off.

vogels.log.level('info'); // enabled INFO log level

Logging can also be enabled / disabled at the model level.

var Account = vogels.define('Account', {hashKey : 'email'});
var Event = vogels.define('Account', {hashKey : 'name'});
 
Account.log.level('warn'); // enable WARN log level for Account model operations

Examples

var vogels = require('vogels');
 
var Account = vogels.define('Account', {
  hashKey : 'email',
 
  // add the timestamp attributes (updatedAt, createdAt) 
  timestamps : true,
 
  schema : {
    email   : Joi.string().email(),
    name    : Joi.string().required(),
    age     : Joi.number(),
  }
});
 
Account.create({email: 'test@example.com', name : 'Test Account'}, function (err, acc) {
  console.log('created account at', acc.get('created')); // prints created Date 
 
  acc.set({age: 22});
 
  acc.update(function (err) {
    console.log('updated account age');
  });
 
});

See the examples for more working sample code.

Support

Vogels is provided as-is, free of charge. For support, you have a few choices:

Ask your support question on Stackoverflow.com, and tag your question with vogels.
If you believe you have found a bug in vogels, please submit a support ticket on the Github Issues page for vogels. We'll get to them as soon as we can.
For general feedback message me on twitter
For more personal or immediate support, I’m available for hire to consult on your project. Contact me for more detals.

Maintainers

Ryan Fitzgerald (@ryanfitz)

License

(The MIT License)

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

vogels

vogels

Features

Installation

Getting Started

Define a Model

Schema Types

UUID

Configuration

Saving Models to DynamoDB

Updating

Deleting

Loading models from DynamoDB

Query

Global Indexes

Local Secondary Indexes

Scan

Parallel Scan

Batch Get Items

Streaming api

Dynamic Table Names

Logging

Examples

Support

Maintainers

License

Private packages for the whole team

Collaborators

Stats

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Dependencies (6)

Dependents