s3-orm

The ORM for AWS S3!

This is a simple object relation model (ORM) that uses S3 as it's storage engine. So why the heck would you want that? End of the day, you should probably use a database. But.... S3 is just a giant key-value store, which means this is possible. So why not?

So this is really just an experiment. But in situations where your data moves slowly, you're dealing with fairly basic queries and you need that massively scalable infrastructure that comes with S3, then this actually works pretty well.

When I started building this, it was originally designed for a simple content management system (CMS). In that case, the website pulls content/data from JSON objects stored on S3 - with the static assets also stored on S3. This means the website will scale massively and is super cheap (i.e. no back-end infrastructure at all, and S3 is dirt cheap).

So it's a crazy idea, but actually proved really useful - but in narrow use cases.

Instalation and Usage

yarn add s3-orm
npm install s3-orm

Documentation

Terminology

• schema: Schema is the data definition for a model, i.e. it describes the data used by a model.
• model: A model is a class that encapsulates the data schema, and allows you to create instances of that model.
• document: This is an instance of a model, i.e. the underlying data decorated with the model methods.
• field: The key of the schema, i.e. the "column" name of your documents.

Schema definition

A schema object is required when defining a model. This is a basic object with key/values where the value is the field defintion. A field definition can consist simply of the field type, or be an object with a type key and other optional values set such as an index. Here is an example of such a schema;

const schema =  {
    email: {type: DataTypes.String, unique: true},
    age: {type: DataTypes.Integer, index: true},
    score: {type: DataTypes.Float, index: true},
    fullName: {type: DataTypes.String, index: true},
    lastIp: DataTypes.String,
    lastLogin: {type: DataTypes.Date, index: true},  
    preferences: DataTypes.Json, 
    tags: DataTypes.Array, 
    level: { type: DataTypes.String, default: 'user', index: true },
    status: { type: DataTypes.String, default: 'active' }
}

Field definition

A field can have the following keys

name	Description
type	The field data type, such as DataTypes.Number
index	Sets an index for a field, i.e. enables you to query on this field
unique	Sets an unique for a field, i.e. enforces uniqueness for this field and enables you to query on it
default	Specify a default value for this field, this can also be a function
defaultValue	Same as default
onUpdateOverride	A function that is called when the document is saved, the field value is set by the output of this function during the save

Field types

DataTypes.Id    // Integer, id field, this is automatically added to all models
DataTypes.Uuid    // String, a uuid v4 field, will generate a uuid automically if no value set during a save
DataTypes.Json    // Json object
DataTypes.Float    // Float
DataTypes.Number    // Integer
DataTypes.Integer    // Integer
DataTypes.String    // String
DataTypes.Boolean    // Boolean
DataTypes.Array    // Simple array of basic types
DataTypes.Date    // Date

Queries

You can query any data type that you have an index set for. If an index is not set, all queries will throw a no-index error. A query is simply an object with key/values that correspond to the query you wish to perform. For numeric and date fields you can use the $gt, $gte, $lte and $lt operators to bound queries. If multiple keys exists, then the query will be a and of all the keys. An or operator is currently not support, but planned for the future. Example queries are;

// Query for all documents where the fullName field contains a substring of 'bob'
qry = {fullName: 'bob'};
// Query for all documents where the fullName field contains a substring of 'ob' (so bob would match this)
qry = {fullName: 'ob'};
// Query for all documents where the age = 20
qry = {age: 20};
// Query for all documents where the age is greater than or equal to 19
qry = {age: {$gte: 19}};
// Query for all documents where the fullName field contains a substring of 'bob' AND the age is greater than or equal to 19
qry = {fullName: 'bob', age: {$gte: 19}};
// Query for all documents where the score is les than 50.56
qry = {score: {$lt: 50.56}};

Query options

Queries (find, findOne, getIds, count, distinct) can be passed additional options, these include;

name	Default	Description
offset	0	Skip the first n documents
limit	1000	Limit the number of returned documents to x
order	'ASC'	The order of the returned results, can be ASC (ascending) or DESC (descending)

Model methods

Instance methods

name	Description
constructor(data)	Create an instance of this model (document), and optionally pass in the initial data
toJson()	Returns the document data as Json
remove()	Delete this document
save()	Save this document to S3

Static methods

name	Description
resetIndex()	Clears all the indices and attempts to rebuild them. Note this can take some time for large data sets
exists(id)	Checks if a document exists with this id (this is faster than using a find)
max(field)	Gets the maximum value for this field name. The field must be a numeric type
count(query)	Gets a count of the number of documents for the given query
distinct(field, query)	Returns an array of disctinct values for the given field. You can optionally pass a querry to restrict the set of documents looked at
remove(id)	Delete a document with the given id
loadFromId(id)	Load a document from the given id
findOne(query, options)	Find and return a single document using the given query and options
find(query, options)	Find and return an array of documents using the given query and options
getIds(query, options)	Same as find, but only returns an array of id's. This is quicker than a find, so good to use if you only need the id's
generateMock()	Generate random test data that matches the model schema

Storm methods

Instance methods

name	Description
constructor(config)	Create a new instance of the s3 ORM ("storm"), passing in config options
define(name, schema, options))	A factory method to create and register a model class
listModels()	Give a list of all the models currently registered

Basic usage

const {Storm, DataTypes} = require('s3-orm');

// You can use in a read-only way with an anonymouse user (useful for browsers)
const config = {
    prefix: 's3orm/',
    bucket: 'theva-test-assets'
};

// OR, for server-side you can use the AWS S3 credentials for full read/write access
const config = {
    prefix: 's3orm/',
    bucket: process.env.AWS_BUCKET,
    accessKeyId: process.env.AWS_ACCESS_KEY_ID,
    secretAccessKey: process.env.AWS_SECRET_ACCESS_KEY
};

// Create an instance of the storm ORM with this engine
const storm = new Storm(config);

// Create a schema
const schema =  {
    email: {type: DataTypes.String, unique: true},
    age: {type: DataTypes.Integer, index: true},
    score: {type: DataTypes.Float, index: true},
    fullName: {type: DataTypes.String, index: true},
    lastIp: DataTypes.String,
    lastLogin: {type: DataTypes.Date, index: true},  
    preferences: DataTypes.Json, 
    tags: DataTypes.Array, 
    level: { type: DataTypes.String, default: 'user', index: true },
    status: { type: DataTypes.String, default: 'active' }
}

// Use the factory method to create the Person class using 
// this schema and any options you want to set
const Person = storm.define('person', schema, {expires: 100});

// You can use the generateMock method to create random data for testing
let pete = new Model();
pete.fullName = 'Pete The Cat';
pete.age = 12;

// Save this instance to S3 (or whatever back-end engine you are using)
await pete.save();

// You can also use the generateMock method to create random data for testing
let randomData = Model.generateMock();
let rando = new Person(randomData);
await rando.save();

// Examples of some basic queries
let people = await Person.find({age: {$gte: 12}});
let people = await Person.find({fullName: 'Cat'});

S3 Setup

If you intend to enable public reads, then you'll need to set the bucket policy and CORS correctly. NOTE to enable directory listing you'll need to add both the bucket and the bucket with the trailing /* into the resource section.

For example;

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "PublicRead",
            "Effect": "Allow",
            "Principal": "*",
            "Action": [
                "s3:ListBucket",
                "s3:GetObject",
                "s3:GetObjectVersion"
            ],
            "Resource": [
                "arn:aws:s3:::<bucketname>",
                "arn:aws:s3:::<bucketname>/*"
            ]
        }
    ]
}

And for CORS;

[
    {
        "AllowedHeaders": [
            "*"
        ],
        "AllowedMethods": [
            "GET",
            "HEAD"
        ],
        "AllowedOrigins": [
            "*"
        ],
        "ExposeHeaders": [],
        "MaxAgeSeconds": 3000
    }
]

Roadmap

• Expires index
• Versioning
• Indexing arrays and json object