Cloudant is an open source non-relational, distributed database service that requires zero-configuration. It's based on the Apache-backed CouchDB project and the creator of the open source BigCouch project.
Cloudant's service provides integrated data management, search, and analytics engine designed for web applications. Cloudant scales your database on the CouchDB framework and provides hosting, administrative tools, analytics and commercial support for CouchDB and BigCouch.
Cloudant is often…
$1
per month per GB of storage above the included 20 GB
MongoDB
Score 8.6 out of 10
N/A
MongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.
$0.10
million reads
Pricing
IBM Cloudant
MongoDB
Editions & Modules
Standard
$1
per month per GB of storage above the included 20 GB
Standard
$75
per month 100 reads/second ; 50 writes/second ; 5 global queries/second
Lite
Free
20 reads/second ; 10 writes/second ; 5 global queries / second ; 1 GB of storage capacity
Standard
Included
per month 20 GB of storage
Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
Offerings
Pricing Offerings
IBM Cloudant
MongoDB
Free Trial
Yes
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
Yes
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
Fully managed, global cloud database on AWS, Azure, and GCP
More Pricing Information
Community Pulse
IBM Cloudant
MongoDB
Considered Both Products
IBM Cloudant
Verified User
Engineer
Chose IBM Cloudant
I have used MongoDB prior to using Cloudant. For me Cloudant is a winner because the learning curve is not as steep as MongoDB. I also looked into using DynamoDB (AWS) but the set up was quite complicated so I gave up and tried to use Cloudant.
Cloudant extends features of CouchDB, but you don't have to host it for yourself. IBM does this for you. Also Cloudant is free if you are under $50 per month. And there is integration with other IBM products, like dashDB (for analytics).Cloudant has CouchApps and it's a feature …
We chose Cloudant because it was fully managed and used in the marketplace, unlike MongoDB was at the time, and it supported JSON which SQL Server 2016 didn't.
The feature-set, including security, is very comparable. Overall, IBM's services added to the product are mature and stable, although product support and engineers could be a little better. Global availability is improving, and Disaster Recover Capabilities are great. Overall, …
The documentation of Cloudant alone has made it my database service of choice. With MongoDB you have to manage hardware, sharding, networking... Cloudant takes all the hassle out of storage allowing you to focus on more important tasks.
MongoDB Atlas and Azure Cosmos DB are the closest competitors we found with Cloudant, especially in terms of fixed pricing and having a GUI for easy viewing and quick edits of data. Cloudant's pricing model flat out beats MongoDB Atlas' in terms of how easy it would be to …
IBM cloudant documentation is very easy to understand and because of that the implementation is also very easy. We found some difficulties in case of aws documents implementation. Performance of the cloudant database is also high as compare to the other databases. Indexing and …
IBM Cloudant is great for quick deployment and configs of a database service, especially when it comes to rapid prototyping. In a research capacity, we need to spin up web services and run experiments quickly. IBM Cloudant is a fuss-free database service [that] aids in this …
I have mainly used Cloudant as I work with IBM Cloud in my role and therefore it was easiest (and cheapest) to set up for the small scale prototypes we are building. (Which do however sometimes lead to scaled implementation)
IBM Cloudant DB is backed by CouchDB and that too hosted on IBM Cloud is the key. Concurrency and durability is the key here. In-memory capabilities are non-existent on the IBM Cloudant DB.
It's easier to use than Dynamo, more open than Firebase, and has better documentation that CouchDB... it might not be fair to compare Modulus, Modulus obviously suffers from some scalability issues and might not be in the same class... but its a hosted DB service we had some …
All other NoSQL document-centric DB must be installed on premise on in the cloud as complicated clusters. The "as a service" formula and the open source origin were the same reasons for Cloudant choice, freeing us of all system and administration tasks!
Cloudant is a database as a service with a strong support team. The feature set is comparable to other solutions but not all are managed services, or have easy scalability, or can demonstrate production level reliability and performance.
The technology behind Cloudant (BigCouch) is no better or worse than any of these. They are all good for different reasons. What makes Cloudant my choice against them is the hosted portion. These are all just databases that I would have to manage. Cloudant is managed for me, …
I've even worked with Cassandra, but I found Cloudant to be much simpler, easier, neat and efficient. Cassandra was not highly scalable but Cloudant was much efficient in it. Even the Monitoring and other scripts were pre-built which made it much time efficient for us.
Our organization found Cloudant most suitable if One, a fixed pricing structure would make the most sense, for example in a situation where the project Cloudant is being used in makes its revenue in procurement or fixed retainer — thus the predictability of costs is paramount; Two, where you need to frequently edit the data and/or share access to the query engine to non-engineers — this is where the GUI shines.
If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.
Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.
An aggregate pipeline can be a bit overwhelming as a newcomer.
There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.
the flexibility of NoSQL allow us to modify and upgrade our apps very fast and in a convenient way. Having the solution hosted by IBM is also giving us the chance to focus on features and the improvement of our apps. It's one thing less to be worried about
I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.
It's mostly just a straight forward API to a data store. I knock one off for the full text search thing, but I don't need it much anyways. Also, the dashboard UI they give is pretty nice to use. It provides syntax-highlighting for writing views and queries are easy to test. I wish other DBs had a UI like this.
NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.
it is a highly available solution in the IBM cloud portfolio and hence we have never had any issues with the data base being available - we also do continuous replication to be on the safer side just in case some thing goes awry. We also perform twice a year disaster recovery tests.
very easy to get started and is very developer friendly given that it uses couchDB analytics. It is a cloud based solution and hence there is no hardware investment in a server and staging the server to get started and the associated delays/bureaucracy involved to get started. Good documentation is also available.
Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.
online resources are good enough to understand but there is nothing like testing. In our case, we discovered some not documented behavior that we take in count now. Also, the experience in NodeJs is critical. Also, take in count that most of the "good practices" with cloudant are not in online courses but in blogs and pages from independent developers
While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.
The feature-set, including security, is very comparable. Overall, IBM's services added to the product are mature and stable, although product support and engineers could be a little better. Global availability is improving, and Disaster Recover Capabilities are great. Overall, it's very comparable to MongoDB as a DBaaS offer, available globally and with great documentation.
We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.
The service scales incredibly well. As you would expect from CloudDB and IBM combination. The only reason I wouldn't score it a 10 is the fact that document trees can get nested and nested very quickly if you are attempting to do very complex datasets. Which makes your code that much more complex to deal. Its very possible we could find a solution to this problem with better database planning to begin with, but one of the reasons we chose a service over a self-hosted solution was so we could set it up quick and forget about it. So we weren't going to dedicate a team to architecture optimization.
Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB