In this project I have implemented the exact same chat application with different local first database technologies. You can use it to compare metrics and learn about the differences. The chat app is a web based angular application, with functionality similar to Whatsapp Web.

• AWS Amplify Datastore
• Firebase Firestore
• PouchDB with IndexedDB adapter & CouchDB replication
• RxDB LokiJS with LokiJS Storage & GraphQL replication
• RxDB Dexie.js with Dexie.js Storage & GraphQL replication
• WatermelonDB with LokiJS adapter (no backend sync atm)

All metrics are measured automatically via code in a browser tests (chrome:headless). The results heavily depend on the developers device. You should compare the values relative to another and not as absolute values. Also you might want to create new metrics that better represent how you would use the respective database.

You can reproduce these values by running sh measure-metrics.sh in the root folder.

• Page load time: How long does it take to download and parse the JavaScript bundle.
• First angular component render: How long does it take for the first angular component to be rendered.
• First full render: How long does it take until all relevant data is displayed for the first time.
• Insert one message: How long does it take to insert a single message.
• Inserting 20 messages one after another: How long does it take to insert 20 messages in serial.
• Inserting 20 messages in parallel: How long does it take to insert 20 messages in parallel.
• Message insert to message list change: How long does it take until a new message is rendered to the dom.
• User change to message list change: How long does it take from changing the user to the displaying of the new messages list.
• Message search query time: How long does it take to search for a given message by regex/like-operator.
• First full render with many messages: Time to first full render when many messages exist.
• Storage usage: Size of the stored IndexedDB database after inserting the full test dataset.
• Bundle size, plain JavaScript: The full JavaScript bundle size, without minification or gzip.
• Bundle size, minified+gzip: The full JavaScript bundle size after minification and gzip compression.

WatermelonDB and the RxDB-LokiJS project use the LokiJS database as storage, which is an in memory database that regularly persists the data to IndexedDB either on interval, or when the browser tab is closed. By doing so, less slow IndexedDB transaction are used. Keeping and processing the data in memory has the benefit of being much faster, but it also has its downsides:

• Initial page load is much slower when much data is already stored in the database, because all data must be loaded before any database operation can be done.
• All data must fit into memory.
• Data can be lost when the JavaScript process is killed ungracefully like when the browser crashes or the power of the PC is terminated.
• There is no multi-tab-support with plain LokiJS. The data is not shared between multiple browser tabs of the same origin. RxDB handles that by adding its own multi tab handling via the BroadcastChannel module.

On the first page load, Firebase ensures that the local data is equal to the server side state. This means that the client has to be online at application startup which is the reason why Firebase is not completely offline first. To ensure the equalness of client side data, Firebase has to perform several requests to the backend, before the database will respond to queries. This makes the inital page load slow, and it becomes even more slower, the more data exists and has to be validated.

For the PouchDB and RxDB (with PouchDB storage) I used the old Indexeddb adapter. It is much less optimized than the new adapter, but the new one made problems with returning the correct query results. Theses problems have been fixed on the PouchDB master branch, but I have to wait for the next PouchDB release. I will update the repo when this change can be done.

AWS Datastore does not save any metadata together with the documents. Instead only the plain documents are stored in IndexedDB. They can do this because they only allow simple queries and do not keep a local version history.

All sub-projects use the same port and so can not be started in parallel.

• You must have installed Node.js
• Clone this project
• In the root folder, run npm install to install the dependencies.
• In the root folder, run npm run build to build all projects.

• Run npm run start:firebase to start the mock server and the production build frontend.

• Or run npm run dev:firebase to start the mock server and the development frontend server.

• Open http://localhost:3000/ to browse the frontend.

The official AWS mock does not allow a live replication at this point. So you first have to setup an amplify project in the ./projects/aws folder by using this tutorial

• Run npm run start:aws to start the mock server and the production build frontend.

• Or run npm run dev:aws to start the mock server and the development frontend server.

• Open http://localhost:3000/ to browse the frontend.

• Run npm run start:pouchdb to start the mock server and the production build frontend.

• Or run npm run dev:pouchdb to start the mock server and the development frontend server.

• Open http://localhost:3000/ to browse the frontend.

• Run npm run start:rxdb-lokijs to start the mock server and the production build frontend.

• Or run npm run dev:rxdb-lokijs to start the mock server and the development frontend server.

• Open http://localhost:3000/ to browse the frontend.

• Run npm run start:rxdb-dexie to start the mock server and the production build frontend.

• Or run npm run dev:rxdb-dexie to start the mock server and the development frontend server.

• Open http://localhost:3000/ to browse the frontend.

• Run npm run start:watermelondb to start the mock server and the production build frontend.

• Or run npm run dev:watermelondb to start the mock server and the development frontend server.

• Open http://localhost:3000/ to browse the frontend.

Pull requests are welcomed. Please help implementing more examples:

• Meteor (with the IndexedDB offline first plugin).
• WatermelonDB backend replication.
• AWS Ampflify local backend mock with realtime replication.
• GunDB.