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  1. Stackups
  2. Application & Data
  3. Platform as a Service
  4. Realtime Backend API
  5. CouchDB vs Firebase

CouchDB vs Firebase

OverviewDecisionsComparisonAlternatives

Overview

Firebase
Firebase
Stacks42.5K
Followers36.0K
Votes2.0K
CouchDB
CouchDB
Stacks529
Followers584
Votes139
GitHub Stars6.7K
Forks1.1K

CouchDB vs Firebase: What are the differences?

<Write Introduction here>
  1. Data model: CouchDB is a document-oriented database, storing data in JSON documents, while Firebase is a NoSQL real-time database that stores data in JSON format but has a hierarchical data structure.
  2. Querying data: CouchDB uses MapReduce for querying data, offering flexibility in querying but requires more manual effort. Firebase uses a real-time database that synchronizes data in real-time with clients, providing automatic data updates but with limited querying capabilities.
  3. Authentication and security: Firebase offers built-in authentication services, which are easy to integrate and manage. On the other hand, CouchDB requires additional configurations and setups for implementing authentication and security measures.
  4. Scalability: Firebase is managed by Google and automatically scales to accommodate large amounts of data and user traffic. In contrast, CouchDB depends on manual configuration for scalability, which can be more complex to manage for larger scale applications.
  5. Conflict resolution: Firebase handles conflict resolution in real-time data synchronization, ensuring data consistency among clients. In CouchDB, conflict resolution needs to be managed manually, which can be more challenging, especially in distributed environments.
  6. Offline capabilities: Firebase provides robust offline capabilities, allowing data to be synced when the connection is restored. CouchDB also supports offline functionality but may require more custom implementation for seamless synchronization.

In Summary, CouchDB and Firebase differ in their data model, querying methods, authentication, scalability, conflict resolution, and offline capabilities in web development.

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Advice on Firebase, CouchDB

Gabriel
Gabriel

CEO at Naologic

Jan 2, 2020

DecidedonCouchDBCouchDBCouchbaseCouchbaseMemcachedMemcached

We implemented our first large scale EPR application from naologic.com using CouchDB .

Very fast, replication works great, doesn't consume much RAM, queries are blazing fast but we found a problem: the queries were very hard to write, it took a long time to figure out the API, we had to go and write our own @nodejs library to make it work properly.

It lost most of its support. Since then, we migrated to Couchbase and the learning curve was steep but all worth it. Memcached indexing out of the box, full text search works great.

592k views592k
Comments
Jared
Jared

Contractor at Insight Global

Aug 9, 2019

ReviewonFirebaseFirebase

I started using Firebase over 5 years ago because of the 'real-time' nature. I originally used to use Real Time Database, but now I use Cloud Firestore. I recommend using the Google Firebase PaaS to quickly develop or prototype small to enterprise level web/mobile applications. Since Google purchased Firebase, it has exploded and it growing rapidly. I also find some level of comfort that it is Backed by Google.

272k views272k
Comments
Noam
Noam

Jul 16, 2020

Needs adviceonNode.jsNode.jsExpressJSExpressJSReactReact

We are starting to work on a web-based platform aiming to connect artists (clients) and professional freelancers (service providers). In-app, timeline-based, real-time communication between users (& storing it), file transfers, and push notifications are essential core features. We are considering using Node.js, ExpressJS, React, MongoDB stack with Socket.IO & Apollo, or maybe using Real-Time Database and functionalities of Firebase.

1.15M views1.15M
Comments

Detailed Comparison

Firebase
Firebase
CouchDB
CouchDB

Firebase is a cloud service designed to power real-time, collaborative applications. Simply add the Firebase library to your application to gain access to a shared data structure; any changes you make to that data are automatically synchronized with the Firebase cloud and with other clients within milliseconds.

Apache CouchDB is a database that uses JSON for documents, JavaScript for MapReduce indexes, and regular HTTP for its API. CouchDB is a database that completely embraces the web. Store your data with JSON documents. Access your documents and query your indexes with your web browser, via HTTP. Index, combine, and transform your documents with JavaScript.

Add the Firebase library to your app and get access to a shared data structure. Any changes made to that data are automatically synchronized with the Firebase cloud and with other clients within milliseconds.;Firebase apps can be written entirely with client-side code, update in real-time out-of-the-box, interoperate well with existing services, scale automatically, and provide strong data security.;Data Accessibility- Data is stored as JSON in Firebase. Every piece of data has its own URL which can be used in Firebase's client libraries and as a REST endpoint. These URLs can also be entered into a browser to view the data and watch it update in real-time.;Real-time Synchronization- Firebase takes a new approach to the way data is moved around an app. Rather than using a traditional request & response model, it works by synchronizing data between devices. Whenever your data changes, all clients are immediately notified within milliseconds. The synchronized data is also persisted, allowing new clients to be immediately updated.;First-class Data Security- Traditional applications intermix security code with application code, whereas Firebase treats security as a first-class feature. You define your security policies in one place using a flexible rules language, and Firebase ensures that they are consistently enforced across all parts of your application. Having all your security logic in one place allows for easy auditing and helps you avoid security mistakes. The safety and security of your data is our top priority.;Automatic Scaling- The Firebase API is built from the ground up for performance and scale. Whenever your data changes, Firebase calculates the minimum set of updates required to keep all your clients in sync. In addition, all Firebase API functions are designed to scale linearly with the size of the data being synchronized. More importantly, Firebase handles all of the scaling and operations for you. Your app will scale from its first user to its first million without any code changes.;Servers are Optional- Firebase can provide all of the data storage, control, and transmission needs of most apps. In many cases, Firebase can completely replace your server and server-side code. This means you no longer need to build complicated backend software and can instead focus on your application logic and your customers.
Terrific single-node database; Clustered database ; HTTP/JSON; Offline first data sync
Statistics
GitHub Stars
-
GitHub Stars
6.7K
GitHub Forks
-
GitHub Forks
1.1K
Stacks
42.5K
Stacks
529
Followers
36.0K
Followers
584
Votes
2.0K
Votes
139
Pros & Cons
Pros
  • 371
    Realtime backend made easy
  • 270
    Fast and responsive
  • 242
    Easy setup
  • 215
    Real-time
  • 191
    JSON
Cons
  • 31
    Can become expensive
  • 16
    No open source, you depend on external company
  • 15
    Scalability is not infinite
  • 9
    Not Flexible Enough
  • 7
    Cant filter queries
Pros
  • 43
    JSON
  • 30
    Open source
  • 18
    Highly available
  • 12
    Partition tolerant
  • 11
    Eventual consistency
Integrations
Trigger.io
Trigger.io
Famo.us
Famo.us
Backbone.js
Backbone.js
Ember.js
Ember.js
AngularJS
AngularJS
React
React
No integrations available

What are some alternatives to Firebase, CouchDB?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Socket.IO

Socket.IO

It enables real-time bidirectional event-based communication. It works on every platform, browser or device, focusing equally on reliability and speed.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

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