Couchbase Reviews

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I am working on Couchbase and Elasticsearch together. We use Couchbase as a family data engine for immigration assistance. We use Elasticsearch to replicate the data in realtime from Couchbase, and then we use the search functionality via Elasticsearch.

We are building a property listing system and when it was created we stored all of the data in Couchbase in realtime. We scrape from different sources and select the data from the user agents, and the property agent as well, and then store it. There is a retrieval method built into Couchbase.

I have found the views to be very valuable.

When using Couchbase, I did not face any issues and I think it's quite straightforward. The documentation is clear for the tools, the query, and the indexing. These are easily understood.

I have not faced any difficulty when using Couchbase. It may be because I am a senior developer, so it might be a problem for a junior developer, but I cannot say anything about them.

The interface is good, the dashboard is good, and the analytics is very good. These features have helped us a lot.

Most of the time, the only issued that I have faced was when we upgraded the Couchbase version. It is very difficult to load the backup of the older version to the newer version.

The only problem with it, I mentioned, the loading data from a different version. For that, we use replication to solve the issue. This is the only bad issue we faced, otherwise it is perfect.

I have been using Couchbase for three years.

Currently, I am using version 6.0.

It's stable. I have not experienced any issues.

It's a scalable solution.

In our organization, we have two to three people using Couchbase, and another two to three developers are using Elastic Search.

Communication with the technical support team is rare because most of the time, our clients have not purchased the enterprise version. We solve the issues on our end to keep the project cost low. The project was not too extensive, so we never needed to contact support.

Previously, we were using MongoDB.

The initial setup was straightforward.

We have deployed this solution onto our own cloud. We installed the Agentpoint and deployed Couchbase onto the enterprise cloud here.

The deployment took a couple of months, and to draw the schema and design the other requirements took three to four months.

I will be using the enhanced version when we set it up for the customer.

We have a team in our organization to maintain this solution.

We evaluated other options as well, but we choose Couchbase for the immediate consistency with Elastic, and the real-time native replication plugin, which is fantastic!

I plan to be using the enhanced version.

I would definitely recommend this solution to anyone who is interested in using it.

The enterprise version is a more stable version. The indexing is very powerful and the N1QL is especially useful when you come from an SQL background. It will be very powerful.

This is why I would recommend Couchbase. To this point, I have never needed anything extra added to it.

I am very happy with this solution, and I would rate Couchbase a nine out of ten.

We use it for data link utilization.

The horizontal scale is a major factor. We want to be able to expand our capacity horizontally.

The failover and failback could be a bit easier. When I looked at it last time, it had to be manually done. It also took over an hour for us to rebalance all the nodes.

It's pretty stable. We like it.

Scalability could be a bit more desirable. We are probably a little hardware limited.

With AWS, it might be better. We're also looking at DynamoDB as a possible replacement.

We also looked at MongoDB, some sort of eMemory, and cache layered with a traditional relational database for performance sake, because we churn a lot of data. We collect for each customer upwards of around 20GB/hour of data. Therefore, performance is important to us, so NoSQL eventually became the obvious choice.

The decision was between this solution and MongoDB. We chose this because it came with N1QL, which is their query language. Whereas MongoDB, at that time, did not come with any sort of query capability.

Couchbase is a good solution to a lot of problems, but you will have to do your own research on it. It does have the scalability. It fits most of our needs. Though, the performance could be quicker and better, especially in the querying process.

We actually have not used it with AWS. We just purchased directly with them, and we have our own hardware. As part of our solution, we are now looking to move some of the solution to AWS. We want to provide solutions to our customers and package it as a product, and it feels like a lot of people are asking for cloud as an option. Therefore, we are looking into cloud deployments instead of on-premise deployments.

I am using Couchbase for searching web services to find user metadata.

The most valuable feature of Couchbase is document indexing. It is better than MongoDB. Additionally, the solution is easy to use.

Couchbase could improve the design of the UI because it should be optimized for viewing statistics or a similar feature.

I have been using Couchbase for approximately two years.

The stability of the solution depends on what environment it is deployed in.

I rate the stability of Couchbase an eight out of ten.

The solution scales well for my usage.

We have five people using this solution in my company.

I rate the scalability of Couchbase an eight out of ten.

I have not used the support from Couchbase. If I encounter issues I used the internet for the use cases that I struggle with to find solutions.

I have used MongoDB previously. Couchbase has an administration panel that is more advanced than MongoDB and allows for more cultivation.

In a runtime environment such as Couchbase, the indexing system can struggle when dealing with large numbers of documents, such as two or three million. This can lead to a delay in the intake of documents. However, I have not used MongoDB in a scenario where such a large number of documents is necessary.

I used Docker to help me set up Couchbase and it was easy. The full process takes 10 to 15 minutes to implement.

I rate the initial setup of Couchbase a ten out of ten.

When considering a NoSQL database, I would recommend MongoDB as the first choice. However, if additional tools or functionalities are needed, then Couchbase may be a better option.

I rate Couchbase a seven out of ten.

In our current project, we use this solution in the healthcare field for the telemedical industry and in other projects in the automation industry.

The valuable features of Couchbase are the many documents and index types, and they made a lot of features available enabling us to use it as a complete solution for our needs.

There are some limitations to the database. The SQL database cannot handle real-time processing for critical IoT scenarios. What we have to do is store our data into the database then code it out, this wastes a lot of time.

We have recently started using the solution.

The solution has been reliable and stable.

We have not attempted to scale the solution at this time because we are a large company that needs more security. We are in the early stages of integrating DTS technology, our chosen security solution, once implemented we will begin scaling Couchbase.

The technical support has been responsive and they provide good support.

The installation could be difficult for some engineers that are brand new to the implementation because the reference documents are much harder to find than other solutions, such as MongoDB.

For the cloud-based solution, there are a number of options available when it comes to the frequency of license payments. You can purchase a license monthly, quarterly, and annually. Since our project includes IoT from another solution this pricing model could be complicated for us.

The price of this solution is better than some of the other competitors.

I have evaluated MongoDB and it is lacking some features that Couchbase has making it a complete solution. With MongoDB, we would need another solution to work alongside it to function the same as Couchbase.

I would recommend this solution to others.

I rate Couchbasean eight out of ten.

There are many shifts and we use Couchbase to log that data whenever they travel from one place to another. We log the data and we merge it in the backend. That's how the application and everything works. If you are a temp person on one shift and you have logged data, we use the nearby API to connect them and to pull and push each other's data. 

We also use Couchbase for Android tablet to the cloud. 

The most valuable features are the ease of application and the merging of data.

I have tried multiple libraries in a demo they provide and it works fine, but when it merges with libraries, it creates a problem.

I have been using Couchbase for six to eight months. 

It is stable.

Couchbase is scalable. There are eight to ten users who use it in my company.

Their support is supportive. 

The initial setup was complex. It was a quick implementation. 

My recommendation of Couchbase would depend on the user's requirements. 

I would rate Couchbase an eight out of ten.