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
IBM Cloud Databases
Score 8.5 out of 10
N/A
IBM Cloud Databases are open source data stores for enterprise application development. Built on a Kubernetes foundation, they offer a database platform for serverless applications. They are designed to scale storage and compute resources seamlessly without being constrained by the limits of a single server. Natively integrated and available in the IBM Cloud console, these databases are now available through a consistent consumption, pricing, and interaction model. They aim to provide a cohesive…
N/A
Pricing
IBM Cloudant
IBM Cloud Databases
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
Cloudant is HIPAA compliant and replicated out of the box. We recommend use of Cloudant vs Mongodb for that purpose. We use Redis only as a session cache.
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.
Less Appropriate Scenario: 1) Small Scale or Low Budget Projects 2) Organizations with limited expertise in cloud technologies may find the learning curve steep, especially if they are not familiar with the IBM Cloud platform 3) If database requirements are highly dynamic and change frequently, the comprehensive features and management provided by IBM Cloud Databases might be overkill. A more flexible, self-managed solution could be preferable for adapting to rapid changes.
The ease of setup was effortless. For anyone with development experience, a few simple questions such as name and login data will get you set up.
The web application to manage cluster settings, billing settings and even introspect the data was simple and most importantly worked all the time. This can not always be said for web interfaces of other products.
Better cost reports, before just increasing to another tier, thus increasing the price. This is critical for early stage startups, where budget is tight.
Add more data center options. As a comparison, a similar service, Aiven.io has dozen more options than Compose (basically all big cloud providers). We moved from AWS to Digital Ocean, which made us stop using Compose, since Compose forces us to be either on IBM or AWS.
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
IBM is our trusted partner which never failed to meet our expectations. Stability, efficiency, usability and security is a must have for our business which is fully provided by IBM Cloud Databases
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.
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.
Support is helpful enough, but we haven't always had questions answered in a satisfactory manner. At one time we realized that Compose had stopped taking database snapshots on its two-per-day schedule, and had in fact not taken one for many days. Support recognized the problem and it was fixed, but the lack of proactive checks and the inability to share exactly what happened has caused us to look elsewhere for production work loads
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
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.
The reason why I choose IBM Cloud Databases is that the IBM cloud toolset is already being used in other functions of the company and by using IBM Cloud Databases, the other cloud tools are better embedded and integrated. If the company is set to use amazon tools, I would go for rds.
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.
