For Couchbase Enterprise, I am performing CRUD operations on vendor data, with the primary uses being filtering data, executing CRUD operations, and migrating data from another database.

I had a use case where I searched for important data across all 10,000 vendors to identify which vendor was missing which data. I performed this task twice, once with Couchbase Enterprise and once with MongoDB. When I used Couchbase Enterprise, the utility that I built worked very efficiently with no failures or lags. Conversely, when I did the same with MongoDB, I often faced connection timeouts and unresponsiveness. I am uncertain whether this was an architectural issue or a database-level issue, but we were using the same configurations. I did not face issues in Couchbase Enterprise, but I experienced them in MongoDB. Later, after increasing the timeout limit, things improved in MongoDB.

I have had several positive experiences with Couchbase Enterprise, such as being able to join two buckets or collections effectively. The N1QL language that Couchbase Enterprise supports is significantly better than what MongoDB offers regarding aggregations. While I can perform cross-collection joining in MongoDB, those lookups become quite messy with large amounts of vendor data, but with Couchbase Enterprise, it is much easier. When I perform migrations or search for missing data across approximately 10,000 vendors, the process feels very straightforward because I am using Couchbase Enterprise. The queries are much more readable and helpful, and when I switched to MongoDB, aggregations became more difficult because operations became messy and complex. Using Couchbase Enterprise feels much easier, and in terms of read performance, I find Couchbase Enterprise faster. Comparatively, I did not have to implement caching when using Couchbase Enterprise because results were faster with simple use cases that did not require much calculation, which was a beneficial feature. I also feel Couchbase Enterprise has many configurations available that I did not explore in MongoDB.

In the ecosystem, MongoDB has many communities available for finding solutions, where I think Couchbase Enterprise lacks.

When I faced issues with Couchbase Enterprise, the community support was not strong. I had to invest considerable time and effort to resolve issues. In contrast, when I faced issues with MongoDB, debugging was faster, and the community support was better. Additionally, I worked on some user interface development for a web application with Couchbase Enterprise, but MongoDB provides an intuitive interface with Compass, making it easier to run queries and understand the application's current state. I also heard from a peer about a complex multi-document transaction requiring strict consistency, which Couchbase Enterprise did not support effectively, whereas MongoDB was mature and predictable for such transactions.

I have been using Couchbase Enterprise for a year.

I have worked with Couchbase Enterprise for a year, and then I shifted to MongoDB due to licensing reasons.

I would rate Couchbase Enterprise an eight out of ten.

Regarding this rating, based on my experiences and the use cases I worked on while using Couchbase Enterprise, I felt it was very good. I was able to understand and comfortably perform use cases, whether data migration or standard CRUD operations. In those cases, I found Couchbase Enterprise truly useful compared to the complex aggregations in MongoDB, although both have solid support. I still felt more satisfied with Couchbase Enterprise for the use cases I worked on, though this is not a generalized view.

Pricing, setup cost, and licensing are outside my area of expertise, but I am aware that we moved from Couchbase Enterprise to MongoDB due to licensing issues.

My main use case for Couchbase Enterprise is to store sessions. Specifically, I utilize the product's session management function to store user experience sessions in Couchbase, and for the profiles so that I can discover the peer node. For long timers, I use Couchbase Enterprise.

A specific example of how Couchbase Enterprise fits into my session management and profile discovery processes is that the session management of the discovery profile functions in distributed systems, where the peer node can change, meaning it's not systematic data that can be stored. Therefore, Couchbase Enterprise is a perfect solution for me to store that session in the database.

The best features Couchbase Enterprise offers for my use cases are user profile and session management.

For user profiles and session management, the features of Couchbase Enterprise that make it stand out for me are its scalability, performance, and flexibility. I would add that Couchbase Enterprise is reliable; being a key-value store makes it especially useful for me. Additionally, it can be set up on Azure, AWS, or on-premise, which is a great feature.

Couchbase Enterprise has positively impacted my organization by being easy to set up and use, making the GUI perfect for everyone, which enhances user experience. This ease of use translates into actual outcomes, such as saving my team time for analytics. The GUI saves me a lot of time since I can directly check the document in the key-value store in JSON format, which allows anyone to access it. Consequently, that reduces team time and errors, with measurable benefits.

There is room for improvement from a perspective of needing enhancements. Couchbase Enterprise is fine and working well, so I do not see much improvement needed from the organizational perspective of where I am working or on the product I am using. The reason I chose nine out of ten is that there should be a dedicated feature that allows it to come up with a single click for the ease of everyone, which is why I leave that one point off.

I have been using Couchbase Enterprise for almost ten years.

Couchbase Enterprise is stable.

The scalability of Couchbase Enterprise is good.

The customer support for Couchbase Enterprise is great.

Couchbase Enterprise has positively impacted my organization by being easy to set up and use, making the GUI perfect for everyone, which enhances user experience.

Our main use case for Couchbase Enterprise involves feature configuration management in the hospitality domain. Ours is a SaaS product, and we expose our product to multiple customers such as Marriott, IHG, and MGM, which are chains of hotels. We differentiate the features based on their subscription plans, such as one billion subscription plan from GMG versus a 500 million subscription plan from IHG. In this way, we use FCAM to identify and configure the features that specific chains are entitled to use, storing these configurations in separate documents in Couchbase for IHG, MGM, and Marriott.

We use Couchbase Enterprise to store NoSQL data. We have a new feature called feature configuration management where we store each document in Couchbase for each chain, maintaining separate repository configurations for each.

Mostly we use Couchbase Enterprise for this use case only.

Couchbase Enterprise offers very fast retrieval of feature configurations, which is why we choose it over other NoSQL databases available. The downtime is very low, something I have observed over the past two and a half years, making it a notable feature.

I have never experienced any downtime with Couchbase Enterprise even with large volumes of data or complex queries. We have big customers such as Marriott who have around 10,000 to 20,000 features configured under their chain, and we have tried retrieving data multiple times, employing batch jobs and cron jobs without facing any latency.

Couchbase Enterprise positively impacts our organization because we have previously encountered issues with different NoSQL databases in the market such as Aerospike and MongoDB. Our use case involves a lot of transactional calls where latency must be minimal; hence we opted for Couchbase Enterprise to ensure API responses occur in less than 100 milliseconds, which has been very effective for our downstream and upstream components.

Since day one with Couchbase Enterprise, I have never exceeded the TPS configured for each API, with response times typically between 30 to 40 milliseconds.

The UI I am using is not very user-friendly. There are no dropdown options, and I have to manually enter the key and its value to retrieve any specific document, so adding some toggles or dropdowns would be an improvement.

The core product is good, and I only have a concern about the UI, so if they can improve that, it would be great.

I have been using Couchbase since two and a half years in our back end application.

Couchbase Enterprise has not shown any low latency in handling peak loads or high user traffic; its performance remains excellent. Couchbase Enterprise is very stable, and we evaluated various options such as MongoDB and Aerospike before concluding that Couchbase Enterprise was the best fit for our needs.

Couchbase Enterprise is very scalable, and we have a configuration such as KEDA to manage incoming traffic, allowing automatic increases in database instances based on user load, which is effective in handling peak traffic.

We have interacted with Couchbase Enterprise's customer support for troubleshooting issues, and my experience with them was positive; they were very helpful.

I would rate the customer support of Couchbase Enterprise a nine.

We previously used another NoSQL database that caused many issues, which led us to migrate to Couchbase Enterprise. After the migration, we have not faced any significant issues, and everything has been running smoothly.

Couchbase Enterprise's documentation and community support are useful for basic setup and common issues, although it may not cover all possible problems.

I did not personally handle the integration since I am part of the backend team, but from what I can observe, integrating Couchbase Enterprise was very simple. The libraries provided a lot of basic retrieve queries, allowing straightforward backend integration.

I do not have much insight into Couchbase Enterprise's pricing, setup cost, and licensing. My team typically manages that data, and from my perspective as a user, I just utilize it and deploy our APIs.

The learning curve for new users of Couchbase Enterprise is very easy. We have available documentation; when we did the integration, we documented everything so new team members can easily access these documents to help them understand Couchbase Enterprise.

Couchbase Enterprise is very secure in protecting our data because, in comparison to other NoSQL databases where we have lost data previously, we have not experienced any issues with Couchbase Enterprise.

I would advise others looking into using Couchbase Enterprise to consider it if they want a stable database with low latency and minimal downtime. I would rate this review an eight overall.

Couchbase Enterprise is a powerful NoSQL database solution designed for scalability and high performance. I have used Couchbase Enterprise specifically for the performance and querying aspects, where I utilized the N1QL query language, which is the official language for Couchbase. This is a significant advantage because it makes querying documents intuitive for developers who already know SQL.

My main use case includes using the built-in cache of Couchbase Enterprise. The built-in cache layer reduces the need for external caching solutions like Redis, which simplifies architecture. Additionally, it has cross-data center replication so that replication across data centers is smooth and adds resilience if anything goes down. It also integrates well with the ecosystem, including modern frameworks and supports SDKs for multiple languages such as Java.

I used the flexible data model in a real-time billing project where there are situations requiring nested data storage. The nesting can be as deep as five layers, and it is easy to fetch data in the nested layers using Couchbase Enterprise.

Couchbase Enterprise is deployed on-premises in my organization. I used this in Amdocs company, which operates in the telecommunication domain. Couchbase Enterprise is high-performance for real-time workloads and has built-in caching, which reduces the need for external systems. It has cross-data center replication which makes global replication straightforward, and it includes the N1QL query language which is very familiar with SQL-like syntax for querying.

The best features Couchbase Enterprise offers in my experience are performance and scalability because it excels at handling large volumes of data with low latency. The distributed architecture makes it easy to scale horizontally, which is crucial for modern distributed applications. Another valuable feature is the flexible data model because it uses JSON format, which allows me to store complex nested data structures without worrying about rigid schemas. Couchbase Enterprise supports cross-data center replication and integrates well with the Java language. The scalability is impressive as it scales effectively and is excellent at handling large volumes of data with low latency, which is critical for modern applications. Couchbase Enterprise has positively impacted my organization, Amdocs, which has been using it for a very long time.

Couchbase Enterprise can be improved by addressing the complex setup. The initial setup and configuration can be tricky and requires careful tuning of cluster settings, memory quotas, and indexes, which I have already faced.

Another area for improvement is the learning curve. Although N1QL is powerful, there is still a learning curve, especially for developers coming from traditional relational databases.

The licensing cost is something to consider as well. Enterprise licensing can be expensive and may not be ideal for startups or smaller organizations.

There is operational overhead with Couchbase Enterprise, such as managing clusters, monitoring performance, and handling failovers, which require strong DevOps expertise. It would be better if it simplified these aspects and provided better documentation.

I have been using Couchbase Enterprise for three years at Amdocs.

Couchbase Enterprise is highly stable.

The customer support for Couchbase Enterprise is good. I faced an issue in the past, and the customer support helped me with the licensing part and assisted me in setting up Couchbase Enterprise. I would rate the customer support 10 out of 10 as I have not faced any issues.

In a different project, I used a different solution. I used MySQL in many different projects, but for the NoSQL part, I am using Couchbase Enterprise for the first time.

I have seen a return on investment with Couchbase Enterprise, as fewer employees are needed. Money is saved because if I use any other NoSQL database, it would cost more. Time is also saved because the N1QL query language is very similar to relational databases and traditional databases, so developers do not need much time learning the N1QL query language.

My experience with pricing, setup cost, and licensing is that Amdocs itself pays the pricing and licensing. The setup cost is costly because it takes time to set up and is complex, so it is not very cost-efficient.

I evaluated other options before choosing Couchbase Enterprise, such as MongoDB, but it cost more than Couchbase Enterprise. MongoDB is something different than Couchbase, which is why the team chose Couchbase Enterprise instead of MongoDB.

My advice to others looking into using Couchbase Enterprise is that I highly recommend it based on my experience. I compared Couchbase Enterprise with MongoDB, and regarding the data modeling aspect, Couchbase uses JSON documents with a built-in key-value store, while MongoDB uses BSON-format JSON documents. The query language is N1QL, which is a SQL-query language, but MongoDB uses its own MongoDB query language, which is difficult to learn for anyone coming from a traditional relational database background. For the replication part, Couchbase uses cross-data center replication, which is good, while MongoDB uses replica set sharding. Couchbase has integrated caching, which is very helpful for fetching data, while MongoDB requires external cache solutions like Redis. I would rate this product an 8 out of 10 overall.

Basically we have clusters, Couchbase clusters, databases, and that is how we use Couchbase with XDCR. All the clusters are set up and then we use Couchbase. It is a complex application setup we use with Couchbase. We have replication and multi-node Couchbase setup.

The very useful feature of Couchbase is the online addition and deletion of nodes which we use because of XDCR replication. We use this very regularly.

Couchbase has an indexing part that is easy to build. We can create indexes in advance, before we have the data, and then we can stack in the data. This is something we use regularly.

The main issue we keep facing from the past couple of years, observing other teams using Couchbase, is that whenever there is an upgrade, we see many issues with compatibility or nodes not interconnecting after the upgrade. The upgrade part should be taken care of very carefully.

We contacted Couchbase support recently when we had a similar issue. They were helping, but it is a critical system and application we have set up. They need to rethink about their upgrade process and improve their validation part after the upgrade.

My team has contacted Couchbase support directly. I think they provide good support, but we prefer a proactive approach rather than reactive because this is not the first time we are facing issues after an upgrade. It has happened two or three times. We need to be very cautious during upgrades, and application teams get worried because of earlier experiences. We need to avoid these situations.

Our team has been using Couchbase for a while, but I started using it only in the last year.

We encounter compatibility issues with JDK and similar technologies whenever we perform upgrades. We had some issues recently.

We contacted Couchbase support recently when we had an issue. They were helpful, but since we have a critical system and application, they need to rethink their upgrade process and improve their validation after upgrades.

My team has contacted Couchbase support directly. They provide good support, but we prefer a proactive approach rather than reactive because this is not the first time we are facing issues after an upgrade. It has happened multiple times, requiring extra caution during upgrades, which causes worry among application teams due to previous experiences.

I worked with other document databases, MongoDB database and Firestore. Each database has its own advantages and disadvantages. When it comes to the deployment part, MongoDB was much easier to deploy, but there are many differences when comparing features.

I worked with other document databases including MongoDB and Firestore. Each database has its own advantages and disadvantages. When it comes to deployment, MongoDB was much easier to deploy, but there are significant feature differences.

I prefer both, but for complex applications requiring minimal downtime, I prefer Couchbase. If there is room for downtime, I would choose MongoDB.

It is a good solution, but as every product needs improvement, this also needs some enhancement. It is a good product. I rate Couchbase seven out of ten.

In another product, I use what they call N1QL, which is a query language, and I use it to check if ads are available to show to a user. In one part of the product, I only use the Sync Gateway, and in another part, I use N1QL to query the database.

It's great because it's very different from MySQL where you have to update tables. With document type databases, you just say there's a new element in your document, and that's fine. It's really good to use.

I'm looking into geospatial applications, and I know that Postgres has it more natively than Couchbase. However, I haven't done any testing yet to determine if I should switch databases or if Couchbase is fast enough with geospatial documents.

Once it's set up, it's easy to use, and there are no headaches. I would recommend it. There might be people I wouldn't recommend it to who don't know anything about Linux or how to set up servers. They might need to go a different route, perhaps to the cloud, which is easier to use.

It's a lot to learn and to wire everything up, but that is with every good product, you've got to study. It's similar to studying English to speak it properly.

That was years ago when I had the enterprise plan, and it wasn't really stable then. I think it was around 2018. They did update, and since then, I haven't had any problems anymore.

I haven't used graphs yet. I use key value and document based functionality, and I actually used it 10 years ago. Now it's second nature to me.

I'll continue to explore using Couchbase, particularly looking into geospatial applications. While I know that Postgres has more native support for those uses, I haven't yet tested if Couchbase is fast enough with geospatial documents.

I rate Couchbase a nine out of ten.

I can see Couchbase is being used for various use cases, primarily to enhance data handling capabilities.

The best thing about Couchbase is its versatility in handling data.

Overall as a tool, I see room for improvement in Couchbase in certain aspects.

I have been using Couchbase for some time now.

When asked about stability issues with Couchbase regarding bugs or system breakdowns, this was specifically discussed.

Regarding the scalability of Couchbase, I think it shows great potential for growth.

For their support, I would rate them a 7 out of 10. I gave this rating because there are some areas where I think they could improve.

The deployment and initial setup of Couchbase is straightforward, though some people might see it as complex.

The question was raised about whether Couchbase is completely free or if there are any hidden fees.

The discussion included whether Cassandra was being used in conjunction with Couchbase.

I am a user of Couchbase and would recommend it to other people. Giving practical insights would be valuable advice for anyone new to Couchbase.

On a scale of 1-10, I rate Couchbase an 8.