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CouchDB vs Mongoose: What are the differences?
<In this Markdown code, we will compare the key differences between CouchDB and Mongoose.>
1. **Data Model**: CouchDB is a NoSQL database that uses a document-oriented data model, storing data in JSON-like documents. Mongoose, on the other hand, is an Object Data Modeling (ODM) library for MongoDB which uses a schema-based approach to model data.
2. **Technology Stack**: CouchDB is written in Erlang and uses the MapReduce indexing for querying data. Mongoose is Node.js-based and provides a simple API for interacting with MongoDB, supporting features like validation, middleware, and hooks.
3. **Scalability**: CouchDB supports horizontal scaling out of the box with its built-in clustering feature, allowing for easy distribution of data across multiple nodes. In comparison, MongoDB with Mongoose requires more manual intervention for scaling, such as sharding or replication setups.
4. **Query Language**: CouchDB uses MapReduce functions or views for querying data, while MongoDB with Mongoose utilizes the MongoDB Query Language (MQL) that provides powerful query functionalities for interacting with the database.
5. **Updates and Schema Flexibility**: CouchDB allows for flexible schema updates and dynamic changes to documents, making it suitable for scenarios where the data structure needs to evolve over time. In contrast, Mongoose enforces a schema definition and provides more control over data validation and structure, ensuring data consistency and integrity.
6. **Community and Ecosystem**: CouchDB has a smaller community compared to MongoDB, which means fewer resources and plugins available for developers. Mongoose, being a part of the vibrant Node.js and MongoDB ecosystem, benefits from a larger community, extensive documentation, and a wide range of third-party libraries and tools.
In Summary, the key differences between CouchDB and Mongoose lie in their data model, technology stack, scalability, query language, schema flexibility, and community support and ecosystem. Each database has its strengths and use cases, catering to different requirements for data storage and management in web development.
Decisions about CouchDB and Mongoose
Gabriel Pa
CEO at NaoLogic Inc · | 10 upvotes · 589.8K views
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.
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Learn MorePros of CouchDB
Pros of Mongoose
Pros of CouchDB
- JSON43
- Open source30
- Highly available18
- Partition tolerant12
- Eventual consistency11
- Sync7
- REST API5
- Attachments mechanism to docs4
- Multi master replication4
- Changes feed3
- REST interface1
- js- and erlang-views1
Pros of Mongoose
- Several bad ideas mixed together17
- Well documented17
- JSON10
- Actually terrible documentation8
- Recommended and used by Valve. See steamworks docs2
- Can be used with passportjs for oauth1
- Yeah1
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Cons of CouchDB
Cons of Mongoose
Cons of CouchDB
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Cons of Mongoose
- Model middleware/hooks are not user friendly3
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- No public GitHub repository available -
What is CouchDB?
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.
What is Mongoose?
Let's face it, writing MongoDB validation, casting and business logic boilerplate is a drag. That's why we wrote Mongoose. Mongoose provides a straight-forward, schema-based solution to modeling your application data and includes built-in type casting, validation, query building, business logic hooks and more, out of the box.
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What companies use CouchDB?
What companies use Mongoose?
What companies use CouchDB?
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What tools integrate with CouchDB?
What tools integrate with Mongoose?
What tools integrate with CouchDB?
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What are some alternatives to CouchDB and Mongoose?
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.
Couchbase
Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands.
Cloudant
Cloudant’s distributed database as a service (DBaaS) allows developers of fast-growing web and mobile apps to focus on building and improving their products, instead of worrying about scaling and managing databases on their own.
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.