Cloudant vs MongoDB

What Cloudant is

IBM Cloudant is a proprietary managed JSON document database built on Apache CouchDB, with a compatible HTTPS API and replication protocol. The Lite plan is free for evaluation and fixes capacity at 20 reads, 10 writes and five global queries per second with 1 GB storage. Standard begins at one provisioned capacity block—100 reads, 50 writes and five global queries per second—includes 20 GB and bills capacity plus excess storage hourly. Dedicated Hardware adds workload isolation, private networking and selected compliance and key-management options. A Cloudant service is not the same as self-hosting CouchDB.

What MongoDB is

MongoDB is the world's most popular NoSQL database, storing data in flexible, JSON-like documents (BSON). It aligns perfectly with modern object-oriented programming, allowing for rapid development without rigid schema requirements. Its 'Atlas' cloud service automates database management and provides global backups. It is ideal for large datasets and fast-evolving application structures where agility is key.

What Cloudant is built to do

JSON document database

Stores schema-flexible documents, attachments and secondary indexes behind HTTPS APIs.

CouchDB-compatible replication

Supports replication patterns between Cloudant regions and compatible CouchDB systems.

Provisioned throughput

Scales read, write and global-query capacity in linked blocks through the dashboard or API.

IBM IAM and SDKs

Integrates IBM Cloud access controls and provides supported Java, Node.js, Python, Swift, Go and mobile clients.

What MongoDB is built to do

MongoDB Atlas

A fully managed multi-cloud database spread across the entire world.

Aggregation

Perform powerful analysis and transformations on your data without code.

Atlas Search

An integrated, Lucene-based professional search engine for your database.

Compass GUI

A desktop tool to visually explore and query your data intuitively.

Choose Cloudant if

• Offline or distributed applications that benefit from CouchDB-style replication
• JSON workloads dominated by key lookups and well-designed partitioned queries
• Teams able to test request-class capacity, 429 handling and multi-region conflicts

Skip Cloudant if

• The application depends on relational joins, broad ad-hoc SQL or multi-document ACID transactions
• Traffic is too unpredictable to provision and monitor request-class capacity
• A free Lite instance is being treated as a production SLA or scalable datastore

Choose MongoDB if

• Learning and prototypes: the M0 free tier gives 512 MB, shared CPU and up to 100 operations per second forever
• Dev and test environments on Flex, $0.011/hour (about $8–$30/month) with 5 GB
• Production apps that need dedicated clusters from $0.08/hour (M10, about $57/month)

Skip MongoDB if

• You need backups on the free tier — M0 has none
• Your workload is heavy: M30 is about $387/month and M50 about $1,440/month before storage, transfer and search add-ons
• You want on-premises Enterprise Advanced with a listed price; it is quoted by sales

Cloudant: pros & cons

• Managed document service: IBM handles database servers, upgrades, patching and core high-availability infrastructure.
• CouchDB lineage: Compatible HTTP APIs and replication ease selected CouchDB application and migration patterns.
• Explicit capacity model: Read, write and global-query throughput are provisioned in documented blocks.
• Multi-region option: Application-managed replication can support active-active regional architectures.
• Lite is evaluation capacity: It cannot scale and blocks new writes above its storage limit.
• Capacity dimensions scale together: A workload dominated by one request class may pay for unused allowances in the others.
• Exceeding throughput returns 429: Applications need retry, backoff and load testing rather than assuming automatic unlimited scale.
• Cross-region is not automatic application resilience: Conflict behavior, traffic routing, monitoring and recovery remain design responsibilities.

MongoDB: pros & cons

• Flexible Schema: No need to redesign tables just to change your data structure.
• High Performance: Very fast for read/write operations, especially with large data.
• Atlas Cloud: A flawless service that removes the pain of installation and maintenance.
• Rich Query Language: Allows for complex data analysis directly within the DB.
• RAM Consumption: Can be heavy on memory usage as it likes to process data in RAM.
• Relational Data: Not as efficient as SQL databases for tasks requiring many 'JOINs'.
• Data Integrity: While ACID-compliant now, SQL is still often preferred for banking data.