Couchbase Capella Reviews

My main use case for Couchbase Capella involves handling data, data analytics, and performing operations with flexible JSON data where low latency is required in real-time applications such as customer profiles, shopping carts, and gaming data. I completed one project in which I analyzed e-commerce data using Couchbase Capella.

In that e-commerce project with Couchbase Capella, we worked with customer data, including customer logs such as customer profiles, their orders, wish lists, and recommendations. This data is structured in JSON format with multiple categories, loyalty points, and product catalog data that includes product ID, name, brand, stock quantities, and prices. We also analyzed customer searches for products, all using Couchbase Capella, which triggered orders, updated inventory, and notified customers.

Regarding the best features Couchbase Capella offers in my experience, I can say that it includes a JSON document database, support for SQL++, high-performance auto-scaling, and vector search, as well as governance features such as security and role-based access control, which I consider to be the best features.

Couchbase Capella has positively impacted my organization by boosting time efficiency and providing fast application response due to its low-latency key-value access, which makes customer order lookups faster and is useful for high-volume transaction applications. It also allows for flexible data models and reduces application complexity, resulting in better stability.

For specifics, I can say that performance is 80% faster, with a four-fold increase in throughput requests and application availability uptime rising from 99.9% to 99.9999%. The application can now handle three times more traffic.

I believe that the documentation should be increased, and features such as vector AI search and other AI capabilities need improvement for Couchbase Capella.

I would say that there is a need for developer experience enhancements, including a simpler user interface, better debugging, SQL++ guidance, and more visibility into granular workload-level costs while reporting.

Couchbase Capella can improve the accuracy and reliability of its AI output. Though it is not guaranteed that the large language model answer will be correct, improvements can be made by grounding the large language models and controlling parameters such as temperature to provide better results.

I have been using Couchbase Capella in my organization for more than one year.

Couchbase Capella is stable in my experience, and we have not faced any issues or downtime.

We have not faced any scalability issues, as Couchbase Capella offers strong horizontal scalability, allowing us to scale the cluster by adding nodes and increasing resources as application traffic and data volume rise.

In terms of customer support, I can say that it is excellent, and we have not faced any issues.

Previously, we did not use any different solutions. We identified the use case and, having completed my certification in Couchbase, knew this was the precise solution rather than using traditional databases.

Our experience with pricing, setup cost, and licensing for Couchbase Capella was relatively straightforward because it is a managed cloud service. The initial setup primarily related to selecting cloud infrastructure, storage, workload requirements, and cluster size, similar to purchasing a traditional database license, with no licensing issues encountered.

I have seen a return on investment. The ROI can be defined in time-saving operations and improved operational efficiency. Before, the database administrator spent twenty hours per week, and now approximately fifty percent of that time has been saved, reducing it to ten to twelve hours per week. Application latency has decreased from five hundred milliseconds to one hundred fifty milliseconds, making it sixty to seventy percent faster.

Before choosing Couchbase Capella, we evaluated traditional SQL databases such as SQL Server but found them lacking in JSON support, flexibility, low latency, and access at scale, which Couchbase Capella provides, leading us to switch.

My advice to others considering Couchbase Capella would be that if your primary use case involves handling flexible JSON with horizontal scaling and near low-latency access, then you should consider Couchbase Capella. I also suggest running a proof of concept using realistic production data and traffic beforehand. I would rate this product an eight out of ten.

The solution is basically used to support our ordering system, which generates a huge number of orders for our customers. 

The way the nodes are managed is interesting. If you want to remove a node, it's much easier to fill it and take it out. You can also add capacity. 

The XDCR is the best feature that I have seen on Couchbase. When you want to start XDCR, stop it, or change a few things in order to filter out the data, it's easy. The XPCR seems to be a very useful and very creative feature. 

It's a one-click solution. You just stop it. You start it, and you're good to go.

There is no rebuilding access as well, and it's quite a hassle for us on other databases. Couchbase monitoring is also fairly easy, thanks to the dashboards that are provided.  

Overall, the backup feature seems very easy. Log collection is easy too. It's very user-friendly. Even for a beginner, it's pretty simple to get started, thanks to the GUI. That helps people get comfortable with it pretty quickly.

The architecture is complex. I do understand that. However, the GUI is very user-friendly. Sometimes all these things are a little difficult to understand for a person who is not experienced in Couchbase.

There is a constant requirement to upgrade the versions. We need to constantly keep on upgrading the latest version for the newest one. Currently, we are dealing with an issue where some of the servers are on the 6.5 version, and a few have moved to 7.5. So we are in a mixed mode right now. We are having a high IO issue on our servers, which we are already dealing with. We have these cases with Couchbase, with Red Hat, et cetera. We feel like this constant need to upgrade is something that is very mundane yet a very difficult task. If you have three clusters, which have around thirty nodes, the data is quite sensitive. Whenever there is Couchbase upgrade that is going on, we see that our SR is dropped. The purchase rate and success rate drop. This affects our business and the clients. 

Rebalancing could be improved. I find it to be a very slow process when it comes to rebalancing the clusters. If you talk about other architectures like Oracle, they are pretty fast. Couchbase is a little slower. Rebalancing, taking the node out, doing the upgrade, putting it back, rebalancing it, is a very difficult and cumbersome. For Oracle, we have been running on version 19.5 for the past five years. There were absolutely no issues. Yet for Couchbase, every six months, we have to go do the upgrade.

I've been using the solution for three years. We've been using it since version 6 and we are now on version 7.5.

The stability is generally good on version 7.5. The clusters operating on that are fine. We're not sure if we're having issues with a different version. Once all of the clusters are upgraded, we will know more about the high IO we've been seeing. CPUs are spking.. We'll be able to determine if 7.5 is stable then or having issues. 

I haven't had any issues with cluster additions. Capacity enhancement is pretty easy.

They have a compaction feature. It helps us greatly since, most of the time, we don't have to handle any disk utilizations manually. It is running in the background, so it is always taking care of that particular component.

We have a team of seven or eight people working on the solution. We're working on a pretty big project and Couchbase is a crucial component.

We have we have platinum support with Couchbase. Every now and then, we speak to the Couchbase representatives. We also conducted a few sessions with them, during which they helped us do health checks for our servers. We also call Couchbase support to get immediate attention. They simply ask us to upload the log as soon as possible, which is a fair ask. 

They are very specific about uploading those logs. This task becomes very difficult in that you have to upload these logs, or some OS whatsoever files, TF files, et cetera. That becomes very difficult for us. Also, I constantly have to run behind the vendors in order to get proper support to get them on calls. Their processes are stringent, wasting a lot of your time. They need to improve their support system.

We did not previously use a different solution. 

The installation is very easy. 

It does cost extra to get platinum support. 

The cost is worth it as the product is well-designed.

We are Counchbase customers. 

Depending on your application, it is good to use Couchbase where you have high OLTP systems where you know there will be constant data loading, deleting, et cetera, happening. It's a good approach to choosing the Couchbase system, and it's fairly easy to use. The main factor to remember is the tuning component in Couchbase. It can be a nightmare if it's not done properly. That said, the resident ratio, for example, the RAM allocations as per the bucket sizing, et cetera, needs to be looked at very carefully while deploying your buckets. Capacity management is something which needs to be looked into. Think long-term and keep adding the capacity as and when it is needed since that will also not be good for the product itself. 

I'd rate the solution eight out of ten.

We use the platform to transfer product pricing, discounts, product types, and location details to different stores.

The platform's most valuable features include the integrated web-based interface, fast querying speed, performance monitors, and flexibility in node scaling. Additionally, the ability to divide services into different clusters and the availability of exhaustive documentation and consultant support are highly beneficial.

The product could be improved by including a log section for tracking activities, enhancing database integration, and providing more transparency regarding pricing and monitoring activities.

We have been using Couchbase Capella for the last six months. 

While the product is generally stable, we have encountered high CPU utilization issues, which we address by adjusting scaling.

Capella offers excellent scalability with its flexible node configuration and the ability to scale vertically and horizontally.

The support team is responsive and knowledgeable, although having a dedicated person familiar with our infrastructure would further enhance the support experience.

We previously used Couchbase Server in-house but switched to Capella to leverage its cloud-based capabilities.

The initial setup was straightforward. 

We implemented Capella in-house, with support from Couchbase consultants who provided valuable assistance.

I rate Couchbase Capella a seven out of ten.