Pros of MongoDB

• Better performance for large-scale applications with high write loads
• More flexible schema design, allowing for easier data model changes
• Stronger support for horizontal scaling and sharding out of the box

Cons of MongoDB

• Less mature ACID transaction support compared to CouchDB
• Potentially higher storage requirements due to document-based structure
• More complex configuration and management for advanced features

Code Comparison

MongoDB query example:

db.collection.find({ status: "active" })
  .sort({ createdAt: -1 })
  .limit(10)

CouchDB query example:

db.find({
  selector: { status: "active" },
  sort: [{ createdAt: "desc" }],
  limit: 10
})

Both databases use JSON-like query syntax, but MongoDB's query language is generally considered more intuitive and powerful for complex operations. CouchDB relies more heavily on MapReduce for advanced querying, which can be more challenging to work with for some developers.

MongoDB excels in scenarios requiring high write throughput and flexible schemas, while CouchDB offers better built-in multi-master replication and a more straightforward approach to eventual consistency. The choice between the two often depends on specific project requirements and scalability needs.

Pros of RethinkDB

• Real-time push architecture for live updates
• Flexible query language with support for JavaScript
• Built-in administration interface for easy management

Cons of RethinkDB

• Smaller community and ecosystem compared to CouchDB
• Less mature and battle-tested in production environments
• Limited support for mobile and edge computing scenarios

Code Comparison

RethinkDB query example:

r.table('users')
 .filter(r.row('age').gt(18))
 .orderBy('name')
 .limit(10)
 .run(conn, callback)

CouchDB query example:

db.find({
  selector: {
    age: { $gt: 18 }
  },
  sort: [{ name: 'asc' }],
  limit: 10
})

Both databases offer JSON-based document storage and support for complex queries. RethinkDB's query language is more expressive and allows for chaining operations, while CouchDB uses a more declarative approach with Mango queries.

RethinkDB excels in real-time applications and offers a more intuitive query language, but CouchDB has a larger ecosystem, better support for offline-first applications, and a more established presence in production environments.

Pros of PouchDB

• Runs in the browser, enabling offline-first web applications
• Lightweight and easy to set up for small to medium-sized projects
• Synchronizes data seamlessly between browser and server

Cons of PouchDB

• Limited scalability for large-scale applications compared to CouchDB
• Fewer advanced features and configuration options
• Potentially slower performance for complex queries on large datasets

Code Comparison

PouchDB (JavaScript):

const db = new PouchDB('mydb');
db.put({
  _id: 'mydoc',
  title: 'Hello PouchDB'
}).then(function (response) {
  // Handle response
}).catch(function (err) {
  console.log(err);
});

CouchDB (HTTP API):

PUT /mydb/mydoc HTTP/1.1
Host: localhost:5984
Content-Type: application/json

{
  "title": "Hello CouchDB"
}

Both PouchDB and CouchDB use similar JSON document structures and RESTful APIs, but PouchDB provides a more JavaScript-friendly interface for browser-based applications. CouchDB, being a full-fledged server database, offers more robust features for server-side operations and scaling.

Pros of OrientDB

• Multi-model database supporting graph, document, key/value, and object models
• Native support for graph operations and traversals
• Better scalability with distributed architecture and sharding capabilities

Cons of OrientDB

• Smaller community and ecosystem compared to CouchDB
• Steeper learning curve due to its multi-model nature
• Less mature replication and conflict resolution mechanisms

Code Comparison

OrientDB (SQL-like query language):

SELECT FROM Person
WHERE name = 'John'
AND age > 30

CouchDB (Mango query):

{
  "selector": {
    "name": "John",
    "age": {"$gt": 30}
  }
}

Both databases offer JSON document storage, but OrientDB provides more flexibility with its multi-model approach. CouchDB excels in ease of use and has a more mature replication system. OrientDB's graph capabilities make it suitable for complex relationship-based data, while CouchDB's simplicity and HTTP API make it ideal for web applications. The choice between them depends on specific project requirements and the desired data model complexity.