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Cloudant vs CouchDB: What are the differences?

Cloudant and CouchDB are both NoSQL databases that are designed to provide horizontal scalability, high availability, and seamless replication. While both databases share many similarities, there are several key differences between Cloudant and CouchDB.

  1. Storage: One of the main differences between Cloudant and CouchDB is the underlying storage mechanism. Cloudant uses a hybrid storage engine that combines the power of both a key-value store and a document-oriented database. This allows Cloudant to provide high-performance querying and indexing capabilities. On the other hand, CouchDB uses a single-file storage model, where each document is stored as an individual file. This can lead to some performance limitations, especially when dealing with large databases.

  2. Deployment Options: Another difference between Cloudant and CouchDB is the deployment options they offer. Cloudant is a managed database service that is hosted in the cloud and fully managed by IBM. This means that users don't have to worry about server management, backups, or infrastructure scaling, as all of these aspects are taken care of by the Cloudant team. CouchDB, on the other hand, can be deployed on-premises or in the cloud, giving users more flexibility and control over their database deployment.

  3. Replication Protocol: Cloudant and CouchDB both support replication, which allows data to be synchronized across multiple instances of the database. However, there is a difference in the replication protocol used by these databases. CouchDB uses a protocol called "Merkle Tree" replication, which ensures that only the changes between the source and target databases are transmitted over the network. This can result in faster replication and reduced bandwidth usage. Cloudant, on the other hand, uses a custom replication protocol that is optimized for their hybrid storage engine. While it still provides efficient replication, it may not be as lightweight as CouchDB's approach.

  4. Integration with IBM Services: Cloudant is part of the IBM Cloud ecosystem and offers seamless integration with other IBM services, such as Watson, Analytics Engine, and Cloud Functions. This allows developers to leverage these services directly from their Cloudant databases and build more powerful applications. CouchDB, on the other hand, is a standalone database and does not provide the same level of integration with IBM services.

  5. Backup and Restore: Cloudant offers automated and incremental backup and restore capabilities, allowing users to easily recover their data in case of any unforeseen events. Cloudant also provides point-in-time recovery, which allows users to restore their databases to a specific point in time. CouchDB, on the other hand, does not provide built-in backup and restore functionality. Users have to rely on manual backup strategies and third-party tools to backup and restore their CouchDB databases.

  6. Data Centers Availability: Cloudant provides global data centers availability, which ensures that users' databases are replicated across multiple geographical locations. This allows for better data availability and disaster recovery in case of any regional outages or failures. CouchDB, on the other hand, does not offer the same level of global data center availability as Cloudant.

In Summary, Cloudant and CouchDB have several key differences, including storage mechanism, deployment options, replication protocol, integration with IBM services, backup and restore capabilities, and data center availability.

Decisions about Cloudant and CouchDB
Gabriel Pa

We implemented our first large scale EPR application from 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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Pros of Cloudant
Pros of CouchDB
  • 13
  • 7
    REST interface
  • 4
  • 3
    JavaScript support
  • 1
    Great syncing
  • 43
  • 30
    Open source
  • 18
    Highly available
  • 12
    Partition tolerant
  • 11
    Eventual consistency
  • 7
  • 5
  • 4
    Attachments mechanism to docs
  • 4
    Multi master replication
  • 3
    Changes feed
  • 1
    REST interface
  • 1
    js- and erlang-views

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What is 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.

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.

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What companies use Cloudant?
What companies use CouchDB?
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What are some alternatives to Cloudant and CouchDB?
Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
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.
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.
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.
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.
See all alternatives