CouchDB vs Pouchdb

Overview

CouchDB

Stacks529

Followers584

Votes139

GitHub Stars6.7K

Forks1.1K

Pouchdb

Stacks148

Followers242

Votes6

GitHub Stars17.5K

Forks1.5K

CouchDB vs Pouchdb: What are the differences?

Introduction

CouchDB and PouchDB are both NoSQL databases that are designed for different purposes. While CouchDB is a server-side database that provides a scalable and distributed architecture for large-scale applications, PouchDB is a client-side database that allows offline functionality and data synchronization with a server-side database. Let's explore the key differences between CouchDB and PouchDB.

Querying Language: One key difference between CouchDB and PouchDB is the querying language they use. CouchDB uses MapReduce for querying, which allows for complex data analysis and aggregation. On the other hand, PouchDB uses a simplified version of MapReduce, called Mango, which provides a simpler and more user-friendly querying language.
Deployment: Another difference is the deployment model of CouchDB and PouchDB. CouchDB is typically deployed on a server and accessed through network connections, making it suitable for large-scale applications with multiple users. PouchDB, on the other hand, is deployed on the client-side, allowing for offline functionality and data synchronization with a remote server, making it ideal for mobile and browser applications.
Data Replication: CouchDB and PouchDB also differ in their approach to data replication. CouchDB provides built-in bidirectional replication, allowing for data synchronization between multiple CouchDB instances. This makes it suitable for distributed and decentralized applications. PouchDB, on the other hand, relies on a synchronization adapter to replicate data with a remote server, providing offline functionality and seamless synchronization with the server-side database.
Storage Size: When it comes to storage size, CouchDB and PouchDB have different capabilities. CouchDB is designed for storing and handling large amounts of data, making it suitable for applications with extensive data requirements. PouchDB, on the other hand, is intended to be used as a lightweight client-side database, and it may have limitations in terms of storage capacity compared to CouchDB.
Security: CouchDB and PouchDB also differ in their security features. CouchDB provides user authentication and authorization mechanisms, allowing for secure access control to the database. It also supports data encryption at the disk level for added security. PouchDB, on the other hand, relies on the security mechanisms provided by the server-side database it synchronizes with. It does not have built-in authentication or encryption capabilities.
Scalability: Lastly, CouchDB and PouchDB differ in their scalability options. CouchDB is designed to be horizontally scalable, allowing for the distribution of data across multiple servers and the ability to handle a large number of concurrent users. PouchDB, being a client-side database, does not have the same scalability options as CouchDB. It relies on the server-side database for scalability and can handle a limited number of concurrent users.

In summary, CouchDB and PouchDB differ in their querying language, deployment model, data replication approach, storage size, security features, and scalability options. While CouchDB is more suited for large-scale applications with complex data requirements, PouchDB is designed for client-side usage, enabling offline functionality and synchronization with a remote server.

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Advice on CouchDB, Pouchdb

Gabriel

CEO at Naologic

Jan 2, 2020

Decidedon

CouchDB

Couchbase

Memcached

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

Detailed Comparison

CouchDB	Pouchdb
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.	PouchDB enables applications to store data locally while offline, then synchronize it with CouchDB and compatible servers when the application is back online, keeping the user's data in sync no matter where they next login.
Terrific single-node database; Clustered database ; HTTP/JSON; Offline first data sync	Cross browser compatibility; Lightweight; Easy to learn; Open source
Statistics
GitHub Stars 6.7K	GitHub Stars 17.5K
GitHub Forks 1.1K	GitHub Forks 1.5K
Stacks 529	Stacks 148
Followers 584	Followers 242
Votes 139	Votes 6
Pros & Cons
Pros 43 JSON 30 Open source 18 Highly available 12 Partition tolerant 11 Eventual consistency	Pros 2 Offline cache 1 Free 1 Repication 1 JSON 1 Very fast

What are some alternatives to CouchDB, Pouchdb?

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

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 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.

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 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

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 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

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 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.

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

Related Comparisons

CouchDB vs Pouchdb: What are the differences?

Introduction

Querying Language: One key difference between CouchDB and PouchDB is the querying language they use. CouchDB uses MapReduce for querying, which allows for complex data analysis and aggregation. On the other hand, PouchDB uses a simplified version of MapReduce, called Mango, which provides a simpler and more user-friendly querying language.
Deployment: Another difference is the deployment model of CouchDB and PouchDB. CouchDB is typically deployed on a server and accessed through network connections, making it suitable for large-scale applications with multiple users. PouchDB, on the other hand, is deployed on the client-side, allowing for offline functionality and data synchronization with a remote server, making it ideal for mobile and browser applications.
Data Replication: CouchDB and PouchDB also differ in their approach to data replication. CouchDB provides built-in bidirectional replication, allowing for data synchronization between multiple CouchDB instances. This makes it suitable for distributed and decentralized applications. PouchDB, on the other hand, relies on a synchronization adapter to replicate data with a remote server, providing offline functionality and seamless synchronization with the server-side database.
Storage Size: When it comes to storage size, CouchDB and PouchDB have different capabilities. CouchDB is designed for storing and handling large amounts of data, making it suitable for applications with extensive data requirements. PouchDB, on the other hand, is intended to be used as a lightweight client-side database, and it may have limitations in terms of storage capacity compared to CouchDB.
Security: CouchDB and PouchDB also differ in their security features. CouchDB provides user authentication and authorization mechanisms, allowing for secure access control to the database. It also supports data encryption at the disk level for added security. PouchDB, on the other hand, relies on the security mechanisms provided by the server-side database it synchronizes with. It does not have built-in authentication or encryption capabilities.
Scalability: Lastly, CouchDB and PouchDB differ in their scalability options. CouchDB is designed to be horizontally scalable, allowing for the distribution of data across multiple servers and the ability to handle a large number of concurrent users. PouchDB, being a client-side database, does not have the same scalability options as CouchDB. It relies on the server-side database for scalability and can handle a limited number of concurrent users.

CouchDB vs Pouchdb

Overview

CouchDB vs Pouchdb: What are the differences?