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…
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MongoDB
Score 8.9 out of 10
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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
Redis Software
Score 9.1 out of 10
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Redis is an open source in-memory data structure server and NoSQL database.
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Pricing
IBM Cloud Databases
MongoDB
Redis Software
Editions & Modules
No answers on this topic
Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
No answers on this topic
Offerings
Pricing Offerings
IBM Cloud Databases
MongoDB
Redis Software
Free Trial
No
Yes
Yes
Free/Freemium Version
No
Yes
Yes
Premium Consulting/Integration Services
No
No
Yes
Entry-level Setup Fee
No setup fee
No setup fee
Optional
Additional Details
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Fully managed, global cloud database on AWS, Azure, and GCP
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More Pricing Information
Community Pulse
IBM Cloud Databases
MongoDB
Redis Software
Considered Multiple Products
IBM Cloud Databases
Verified User
Engineer
Chose IBM Cloud Databases
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 It felt outdated and cumbersome.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.
Aiven backup options are very limited (you can't download backups and you don't have an API) and their dashboard is incomplete and without an optimal design; but they accept way more data centers, and they have more pricing options.
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.
We currently use both Heroku and Compose. Heroku is our PAAS choice for our application servers. As mentioned, previously, the cost of some compose services for development / staging / testing servers was getting costly. For these type of servers we don't need the high …
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.
In our early development days we weighed NoSQL databases like MongoDB with RDBMS solutions like MySQL. We were more familiar with MySQL from past experience but also were wary of painful data migrations that slowed down development iterations and increased the risk of outages …
MongoDB is our go-to database solution for any project, and the more we work with it the more we love it. Some say that NoSQL is pointless... Our developers wholeheartedly disagree, because they love working with it. Though both NoSQL and SQL have their purposes, in most …
MySQL is a great for querying related data, but it's unable to store structured data and has a fixed schema. Also SQL can be non-intuitive. DynamoDB, CouchDB and Redis all make querying the data quite difficult and lack important features. The problem CouchDB tries to solve is …
Verified User
Project Manager
Chose MongoDB
MongoDB is document oriented, and fits our goals best.
Redis Software
Verified User
Technician
Chose Redis Software
Initially, we were unsure whether to use Redis or MongoDB., in reality, they are both no-SQL databases but can be used both as needed. certainly, in my opinion, it is more reasonable a DB no SQL MongoDB than Redis, the key logic value of Redis is certainly performing for the …
Redis is great at set operations and is very fast. Riak is a fast long-term data store, but it is expensive to run. MongoDB is good for small, quick projects. Elasticsearch is great at indexing and searching. Choose the right tool for the job, and don't be afraid to …
Redis was initially in the list of competitors like Aerospike, Cassandra, MongoDB.The major point that outset all others is that it provides a number of read and writes to the database that no one can match. Another major factor is Redis really knows the basic components that …
Couchbase doesn't keep up with what they offer and what really does. MongoDB just doesn't scale out, reads are performed across multiple nodes but writes still go to the single master. DynamoDB is good overall but just way too expensive.
Every time you don't need a document DB, you can't go wrong with Redis over MongoDB. Google Cloud Pub/Sub may have solved one use case, but we'd still have to deploy Redis instances for other use cases, and adding another tech stack would only add complexity to our …
Redis is faster, provides documents JSON-wise with the proper odule and it is far more stable than MongoDB (we had really bad experiences with Mongo, especially when ops tends to increase).
Vice President, Chief Architect, Development Manager and Software Engineer
Chose Redis Software
All are good products. MongoDB is a great NoSQL DB but didn't seem to have the high performance caching of Redis. Coherence and Xtreme Scale are expensive. In my opinion for our particular use case, Redis was the clear winner.
We initially used Memcached for some of the caching and locking solutions we now use Redis for; we found that for the purposes of our system Memcache could not match up to Redis for performance. We also found Redis to be a bit more reliable, but that could have just been down …
We are big users of MySQL and PostgreSQL. We were looking at replacing our aging web page caching technology and found that we could do it in SQL, but there was a NoSQL movement happening at the time. We dabbled a bit in the NoSQL scene just to get an idea of what it was about …
We initially tried ElastiCache with Redis hosting. While it did the job of running Redis, we still had to deal with server sizing. We switched to Redis Cloud since that had auto-scaling and easy to use tools.
One key feature: easy to use. you can install and use it under minutes. For the rest of the options, you have to do more configuration and settings. Besides all these, Redis is in-memory so the performance is a blast. Considering that simple is better, the proof of the concept …
Redis is easy to get setup, has great documentaiton, and quality online support. Antirez is constantly making feature updates the product, and is engaged with the community. Redis doesn't have a lot of bells and whistles, but what features it does has are well implemented and …
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.
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.
Redis has been a great investment for our organization as we needed a solution for high speed data caching. The ramp up and integration was quite easy. Redis handles automatic failover internally, so no crashes provides high availability. On the fly scaling scale to more/less cores and memory as and when needed.
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.
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.
Easy for developers to understand. Unlike Riak, which I've used in the past, it's fast without having to worry about eventual consistency.
Reliable. With a proper multi-node configuration, it can handle failover instantly.
Configurable. We primarily still use Memcache for caching but one of the teams uses Redis for both long-term storage and temporary expiry keys without taking on another external dependency.
Fast. We process tens of thousands of RPS and it doesn't skip a beat.
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.
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.
We had some difficulty scaling Redis without it becoming prohibitively expensive.
Redis has very simple search capabilities, which means its not suitable for all use cases.
Redis doesn't have good native support for storing data in object form and many libraries built over it return data as a string, meaning you need build your own serialization layer over it.
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
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.
We will definitely continue using Redis because: 1. It is free and open source. 2. We already use it in so many applications, it will be hard for us to let go. 3. There isn't another competitive product that we know of that gives a better performance. 4. We never had any major issues with Redis, so no point turning our backs.
IBM Cloud Databases' pricing structure is easy to understand, and if you choose the right product, you can operate your system at minimal cost. Although there is ample documentation available, there doesn't seem to be a user community running on it, so specific usage know-how and troubleshooting can sometimes take longer than expected.
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 quite simple to set up for the purpose of managing user sessions in the backend. It can be easily integrated with other products or technologies, such as Spring in Java. If you need to actually display the data stored in Redis in your application this is a bit difficult to understand initially but is possible.
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
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.
The support team has always been excellent in handling our mostly questions, rarely problems. They are responsive, find the solution and get us moving forward again. I have never had to escalate a case with them. They have always solved our problems in a very timely manner. I highly commend the support team.
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 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.
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.
We are big users of MySQL and PostgreSQL. We were looking at replacing our aging web page caching technology and found that we could do it in SQL, but there was a NoSQL movement happening at the time. We dabbled a bit in the NoSQL scene just to get an idea of what it was about and whether it was for us. We tried a bunch, but I can only seem to remember Mongo and Couch. Mongo had big issues early on that drove us to Redis and we couldn't quite figure out how to deploy couch.
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
Redis has helped us increase our throughput and server data to a growing amount of traffic while keeping our app fast. We couldn't have grown without the ability to easily cache data that Redis provides.
Redis has helped us decrease the load on our database. By being able to scale up and cache important data, we reduce the load on our database reducing costs and infra issues.
Running a Redis node on something like AWS can be costly, but it is often a requirement for scaling a company. If you need data quickly and your business is already a positive ROI, Redis is worth the investment.