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
MongoDB
Score 8.4 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 Cloud Databases
MongoDB
Editions & Modules
No answers on this topic
Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
Offerings
Pricing Offerings
IBM Cloud Databases
MongoDB
Free Trial
No
Yes
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
Fully managed, global cloud database on AWS, Azure, and GCP
We use Amazon's RDS (MySQL database), Redislabs (Redis) and also MongoDB's Atlas. They all have their own advantages and disadvantages. For us, MongoDB's Atlas and Compose are obviously similar services. For now, we use Atlas to try new things (since they run the latest stable …
I tried MLab and was not a fan of how the UI worked on their control panel. It felt outdated and cumbersome. They offered less backup solutions for the price point as well. In fact, you had to contact them with a ticket if you wanted access to a daily backup. Anything over that …
MongoDB is the primary db we use, and Meteor is the primary application framework. Configuring MongoDB to fully support Meteor oplog tailing is a challenge - and when we started looking, Compose was those only MongoDB provider that had turnkey support for Meteor.
We previously hosted our own Redis and RabbitMQ cluster. Before switching to IBM Compose we evaluated Redis Lab, Scalegrid, AWS ElastiCache, CloudAMQP and others. We still host our core database (MongoDB) ourselves.
All our databases are hosted on Compose. We haven't seen a reason to switch providers, however, we have compared with some others and Compose seems to be the best from a cost and reliability standpoint.
While at the time, Amazon RDS did/does not create Mongo databases, I was able to set up many with PostgreSQL databases with the same ease as IBM Compose. However, IBM compose does seem to offer a more intuitive application control panel. Amazon RDS costs run on a server …
We selected Compose because we initially thought that they would provide great support, and that they would bring encryption at rest within months. That has not materialized yet.
We also thought that the cost, while far from being the lowest, was reasonable.
We use Amazon Aurora as our primary datastore and use IBM Compose Mongo as an alternative only when Aurora does not cover the use case well. Amazon DynamoDB looks good but doesn't have the same wealth of libraries and support which makes MongoDB easy to use and therefore was …
We have one instance of mLab that has been equally easy to scale as Compose, but with the added benefit of extensive logging and performance monitoring tools, including an index suggester. All modern cloud db providers seem to offer more of this type of functionality at this …
Other options are lower priced, however IBM Compose has by far the best interface for managing and editing data within the database. It also has many forms of databases for us to deploy, beyond what we are currently using. So, in the event we need to add other services, we can …
We initially selected IBM Compose because it was easy to use and cost-effective. We switched to mLab when we need to scale and have dedicated clusters.
Mongo Atlas - at the moment it looks better. It has 3.6 (Compose stuck at 3.4). Lower pricing (it seems). AWS Dynamo DB etc - I decided rather quickly not to use this, mostly for lack of adequate documentation.
We had used mlab at one point but found it less reliable than compose.io. Really, we wanted a strong foundation to start from day one and figured a produced backed by IBM would be the way to go. We are still a small startup and don't have a ton of resource to mess around with …
I love IBM compose for its simplicity, reliability, scalability, and price. I am uncertain on how the infrastructure is deployed and fault tolerance as we rarely need this.