Couchbase is a distributed NoSQL database platform that combines a JSON document store with a high-performance In-Memory architecture. The solution is designed to support high-throughput applications by integrating multiple data services—including Key-Value, Full-Text Search (FTS), Vector Search, and Real-Time Analytics—within a single unified platform.
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IBM Cloud Databases
Score 8.1 out of 10
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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…
The project we are developing with Couchbase, was very inconsistent for few years of the beginning. We had to change data model multiple times. We knew this before starting the project. So we had to choose a NoSQL solution. We also wanted a syncing solution. After some research …
Couchbase could outperform it's competition considerably for database reads and writes. Full text searches were still faster in Elasticsearch but this is more of a feature than a base platform requirement for us.
At the time, Couchbase seemed the most mature of the NoSQL products and would allow us to achieve the goal of improving data access times for our products and services, giving the most benefit to our customers. MySQL was starting to be the bottleneck in our system performance …
Easy to deploy and manage. Clustering and replication is fairly simple and straightforward. According to developers, Couchbase scored higher points compared to the other products that we evaluated.
The Apache Cassandra was one type of product used in our company for a couple of use-cases. The Aerospike is something we [analyzed] not so long time ago as an interesting alternative, due to its performance characteristics. The Oracle Coherence was and is still being used for …
Single console for managing multi-cluster and multi-cloud deployment options and [the] ability to secure and isolate database information in a secure environment to prevent undefined access is great. Analyzing and delivering information and fast access and processing data …
Experience with DataStax Cassandra was seamless, but the cost and effort to support it was not justified. Also commercial process experience with Couchbase was much better. ActiveSpaces is a good technology for big TIBCO shop, but keeping with the lifecycle of it is not easy. I …
A strategic company, upcoming products, enhanced concepts. Couchbase is a single platform offering many different smaller products together viz Full-Text Search, Analytics, Eventing, Indexing, Querying, Integration with other products.
When launching the system, using multiple services would have been inefficient, so we consolidated it on IBM Cloud Databases. We regularly compared the services provided by IBM Cloud Databases' PaaS with those of other cloud services, but decided that there was no need to go to …
a powerful storm disrupted power supplies and network connections to the data center hosting our critical databases. Despite the external factors causing widespread service disruptions, IBM Cloud Databases demonstrated its exceptional reliability. The auto-failover feature …
UI is easier to use and flexible. AWS EBS is very simple to use and do upgrades and monitor the upgrades easily. I also recommend IBM to implement these.
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 …
IBM cloud database has a lot of features than amazon dynamodb. This is my personal opinion. But I can't say amazon dynamodb is a bad one. But IBM cloud database has a lot of securities and file storage and backup features than amazon dynamodb. But both are good in their own …
I have used Amazon DynamoDm and compared to IBM Compose, I would say IBM Compose is affordable, easy to use and very fast as well. I would opt IBM Cloud Databases given the two choices
they do a great job at handling our business needs. we like what they offer and how they respond to questions we provide. they do a lot of great things that help our business thrive and stay ahead. we are grateful for how this compnay has responded to our unique requests and …
We already had existing contracts with IBM and Microsoft, so those made the most sense to verify. Both are good options for data storage. Since much of our existing Dbs are IBM related, we stuck with IBM cloud dbs, just so that the SQL code would port well. Additionally, we …
The kubernete service is the front end for the transactions of our core systems and our cloud databases (Postgres and DB2) are the persistence storage.
It is very similar to the way on which we operated before except that we don't have to worry about high availability, backups …
AWS RDS & Oracle OCI. AWS RDS has a wider range of databases but at a higher cost. IBM Compose has fewer databases but is perfect for data related solutions like data warehousing (IBM Db2 AI enabled Warehouse is a GREAT product!)
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.
We have Cassandra database that is currently not available as part of IBM Cloud Databases. We ended up using classic infrastructure IaaS to host our Cassandra server.
I did compare IBM Compose for PostgreSQL with PostgreSQL offerings available from Amazon and Google. IBM Compose was judged easier to provision and maintain.
I'm pleased with the additional more granular provisioning flexibility and more favorable cost structure that has come …
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.
Best suited when edge devices have interrupted internet connection. And Couchbase provides reliable data transfer. If used for attachment Couchbase has a very poor offering. A hard limit of 20 MB is not okay. They have the best conflict resolution but not so great query language on Couchbase lite.
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.
Cluster sizing during the design phase can be improved, especially if the client lacks prior experience. Vendor consultants are very meticulous in order to provide best of class performance and response time, although some more real-world pragmatic approach is often needed.
Couchbase Lite 2 went thru a major revamp, which broke the compatibility of the applications with some features removed and other changed. That needed development teams working to refactor the applications.
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.
I rarely actually use Couchbase Server, I just stay up-to-date with the features that it provides. However, when the need arises for a NoSQL datastore, then I will strongly consider it as an option
Couchbase has been quite a usable for our implementation. We had similar experience with our previous "trial" implementation, however it was short lived.
Couchbase has so far exceeded expectation. Our implementation team is more confident than ever before.
When we are Live for more than 6 months, I'm hoping to enhance this rating.
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.
One of Couchbase’s greatest assets is its performance with large datasets. Properly set up with well-sized clusters, it is also highly reliable and scalable. User management could be better though, and security often feels like an afterthought. Couchbase has improved tremendously since we started using it, so I am sure that these issues will be ironed out.
I haven't had many opportunities to request support, I will look forward to better the rating. We have technical development and integration team who reach out directly to TAM at Couchbase.
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
Couchbase could outperform it's competition considerably for database reads and writes. Full text searches were still faster in Elasticsearch but this is more of a feature than a base platform requirement for us.
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.
So far, the way that we mange and upgrade our clusters has be very smooth. It works like a dream when we use it in concert with AWS and their EC2 machines. Having access to powerful instances along side the Couchbase interface is amazing and allows us to do rebalances or maintenance without a worry
There have been several areas of our application [that] really needed an ACID compliant database (e.g. strong transactional guarantees) that we thought we could work around while using Couchbase. [In my opinion] that turned out to be a poor bet. You need to be certain that the specific characteristics of a NoSQL database fit your problem.
Couchbase does eliminate the need for schema upgrades completely. I.e no downtime or conversion windows as you migrate your data model, adding attributes, etc. This helped with the deployment timeframe associated with DB changes.
The database is (apparently) a bit more of a space/memory consumer than originally anticipated. During deployments, we received constant pressure from Couchbase consulting teams to eliminate/reduce the number of indexes, and this was because any mutations to docs in a bucket must check for impact against all indexes. More recent years have started to address this with their "collections" features, which helps isolate indexes to specific sub-groupings of documents.