Couchbase Server vs. DataStax Enterprise

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.

Incentivized

DataStax has a good scalable option with multiple clusters and a good write rate. Cassandra also is improving and is an open-source technology that has good community support. The UI is also easy to understand and implement required functions.

Incentivized

• Easy to store unstructured data and has great performance
• Managing security is super easy which can be managed across different levels
• UI is pretty simple to use and manage the cluster
• Backup of the data is very easy and the restoration/recovery is fairly easy as well with the in-built tools.
• Easy integration with elasticsearch for replication
• It is fairly easy to scale up or scale down the cluster

Incentivized

• Datastax Cassandra provides high availability and good performance for a database. It is built on top of open source Apache Cassandra so you can always somewhat understand the internal functioning and why.
• Datastax Cassandra is fairly simple to start using, you can install/setup your cluster and be productive in 1 day.
• Datastax Cassandra provides a lot of good detailed documentation, and when starting, the detailed free videos on the Datastax site and documentation are very helpful.
• Datastax Enterprise Edition of Cassandra provides more tools, good support, and quick response SLA for enterprise business support.

Incentivized

• 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.

Incentivized

• Cassandra is a bit difficult to learn and understand
• The costs are slightly higher for our company
• Hardware requirement is moderate to high at the beginning

Incentivized

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

Incentivized

We will continue to use it because it scales well with commodity hardware and we are satisfied with the documentation and support.

Incentivized

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.

There is a bit of a learning curve and tasks that are simple in traditional RDBMS systems can be complicated with DataStax Enterprise but once you get the hang of denormalizing data and getting the data model correct DataStax Enterprise is very usable. Usability from the developer's standpoint is very simple - the complication is on the architecture side with the data model.

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.

Incentivized

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.

We have had a few situations where we caused an outage or something has gone wrong and we are able to get a support person to offer live help within minutes. The escalation process is excellent - the best I've seen - and the support team is incredibly strong. Outside of emergencies, the team is very helpful with general questions and working through data model exercises and the subscription I believe still comes with some hours to help get the data model reviewed.

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.

Incentivized

I believe DataStax Enterprise is the best in class. There are some things that are different with the schema-less systems but I found DataStax Enterprise easiest to implement while evaluating. The replication is on par or better than others in practice. We are evaluating Astra in our test environment and that has additional benefits we are looking forward to using.

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

Incentivized

• 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.

Incentivized

• Highly Scalable Database, Highly Available Services, and Platforms.
• High Performance, Low Latency and Highest throughput across varying workloads.
• Configured, Tuned and Monitored correctly works to provide the best user experience!
• Negative: Maintenance and Debugging Corner Cases

Incentivized