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    Couchbase Enterprise Edition Server on Amazon Linux 2 - Graviton

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    Sold by: Couchbase 
    Deployed on AWS
    Couchbase Server is a NoSQL database that delivers unparalleled performance at scale, on premises and in any cloud. It features memory-first architecture, built-in cache, geo-distributed deployment, and workload isolation.
    4.3

    Overview

    Couchbase Server is a NoSQL database that delivers unparalleled performance at scale, on premises and in any cloud. It features memory-first architecture, built-in cache, geo-distributed deployment, and workload isolation. Couchbase excels at supporting business-critical applications at scale while maintaining submillisecond latencies.

    Highlights

    • Multi-Dimensional Scaling (MDS): One size never fits all when it comes to scaling your business. MDS delivers revolutionary distributed architecture providing compute, storage, and processing workload partitioning to meet ever-changing requirements.
    • Eventing: Couchbase Eventing enables user-defined business logic to be triggered in real-time on the server when application interactions create changes in data.
    • Analytics: Use SQL++ based N1QL for Analytics to run ad-hoc analytical queries on operational data while leveraging an MPP query engine. All without impacting operational application performance by maintaining workload isolation.

    Details

    Delivery method

    Delivery option
    Deploy Couchbase Server with CFT
    64-bit (Arm) Amazon Machine Image (AMI)

    Latest version

    Operating system
    AmazonLinux 2.0.20200904.0 Update

    Deployed on AWS
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    Pricing

    Couchbase Enterprise Edition Server on Amazon Linux 2 - Graviton

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    Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time. Alternatively, you can pay upfront for a contract, which typically covers your anticipated usage for the contract duration. Any usage beyond contract will incur additional usage-based costs.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.

    Usage costs (145)

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    • ...
    Dimension
    Cost/hour
    c6g.xlarge
    Recommended
    $0.662
    r8g.large
    $0.662
    r8g.8xlarge
    $1.641
    t4g.2xlarge
    $1.641
    r6g.xlarge
    $0.662
    r6gd.large
    $0.662
    r6gd.8xlarge
    $2.579
    r6g.12xlarge
    $3.319
    r7g.large
    $0.662
    m6gd.4xlarge
    $1.641

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    Legal

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    Usage information

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    Delivery details

    64-bit (Arm) Amazon Machine Image (AMI)

    Amazon Machine Image (AMI)

    An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.

    Additional details

    Usage instructions

    If using the sample CloudFormation template, you may login to the web UI with a browser to port 8091 as Administrator.

    The IAM role "CouchbaseRole" grants the following access permissions:

    Assume Role Permission: The role allows EC2 instances to assume it through the sts:AssumeRole action. Principal: "ec2.amazonaws.com"

    Policies attached: CouchbasePolicy: Grants permissions to: Create and describe EC2 tags. Describe EC2 instances. Describe Auto Scaling Groups. Resource: All EC2 and Auto Scaling resources ("Resource": "*")

    CouchbaseSecretPolicy: Grants permission to: Retrieve secret values from AWS Secrets Manager via the secretsmanager:GetSecretValue action. Resource: The resource reference CouchbaseSecret.

    CouchbaseRallyParameterPolicy: Grants permissions to: Create or update parameters in AWS Systems Manager Parameter Store (ssm:PutParameter). Retrieve parameters from Parameter Store (ssm:GetParameter). Add tags to SSM resources (ssm:AddTagsToResource). Resource: All Parameter Store resources ("Resource": "*").

    In summary, this IAM role gives Couchbase-related EC2 instances permissions to interact with EC2, Auto Scaling, Secrets Manager, and Systems Manager (Parameter Store) for resource management, secret retrieval, and parameter handling in the AWS environment.

    Support

    Vendor support

    This option includes a product license and Silver support. Please checkout our website at https://www.couchbase.com/support-policy/enterprise-software  for details on our Enterprise support subscriptions tiers. For custom pricing or a private contract, please contact cloud_marketplace_orders@couchbase.com , for a private offer. Couchbase provides enterprises with access to 24 x 365 global support to help you in your Couchbase journey. For questions about support please reach out at

    AWS infrastructure support

    AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.

    Product comparison

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    Updated weekly

    Accolades

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    Top
    10
    In Analytic Platforms, Databases & Analytics Platforms, Databases
    Top
    10
    In High Performance Computing, Data Warehouses
    Top
    25
    In Data Warehouses

    Customer reviews

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    Sentiment is AI generated from actual customer reviews on AWS and G2
    Reviews
    Functionality
    Ease of use
    Customer service
    Cost effectiveness
    Positive reviews
    Mixed reviews
    Negative reviews

    Overview

     Info
    AI generated from product descriptions
    Multi-Dimensional Scaling Architecture
    Distributed architecture providing compute, storage, and processing workload partitioning for independent scaling of different resource types
    Real-Time Event Processing
    User-defined business logic triggered on the server in real-time when data changes occur in the database
    Memory-First Architecture
    Database architecture optimized for in-memory performance with built-in cache capabilities
    Analytical Query Engine
    SQL++ based N1QL query language with MPP query engine for ad-hoc analytical queries on operational data
    Workload Isolation
    Capability to maintain separation between operational and analytical workloads to prevent performance impact
    Sub-millisecond Latency Performance
    Delivers linear sub-millisecond performance scaling from gigabytes to petabytes without requiring code modifications
    Multi-Model Data Support
    Supports key-value, JSON document, SQL access, and can handle graph and time series data models
    Geo-Distributed Architecture
    Enables globally distributed applications through geo clustering and cross datacenter replication (XDR) supporting active-active and active-passive design patterns
    NoSQL Database Engine
    Multi-model NoSQL real-time database platform designed for large-scale JSON and SQL use cases
    Predictable Performance Scaling
    Maintains predictable performance characteristics at any scale with industry-leading uptime and reduced infrastructure requirements
    Multi-Region Deployment
    Available across 31+ AWS regions for global application deployment and high availability
    Native Vector Search
    Embedded vector search capabilities for storing, indexing, and querying vector embeddings without requiring a separate vector database
    Device Synchronization
    Fully managed device-to-cloud synchronization solution for mobile application data consistency
    Compliance and Security Standards
    Built-in security features with compliance certifications including HIPAA, GDPR, ISO 27001, and PCI DSS
    Multi-Workload Support
    Handles transactional workloads, app-driven analytics, full-text search, stream data processing, and AI-enhanced experiences within a unified platform

    Security credentials

     Info
    Validated by AWS Marketplace
    FedRAMP
    GDPR
    HIPAA
    ISO/IEC 27001
    PCI DSS
    SOC 2 Type 2
    No security profile
    No security profile
    -

    Contract

     Info
    Standard contract
    No
    No

    Customer reviews

    Ratings and reviews

     Info
    4.3
    147 ratings
    5 star
    4 star
    3 star
    2 star
    1 star
    56%
    38%
    5%
    1%
    0%
    6 AWS reviews
    |
    141 external reviews
    External reviews are from G2  and PeerSpot .
    Andlib Saif

    Distributed workflows have improved real-time validation and now deliver faster, reliable testing

    Reviewed on Apr 05, 2026
    Review from a verified AWS customer

    What is our primary use case?

    I have used Couchbase Enterprise  in a different way. I used it in Informatica to set up an end-to-end flow for the connector. Informatica used to connect to Couchbase for all three applications: IICS Cloud and Informatica.

    Couchbase is running on a Linux server, then I connected using Informatica connectors and evaluated how the connector works with different bucket sizes. I focused on low latency using high-performance NoSQL stores, data validation, integrating Couchbase with PySpark and Great Expectations. I performed end-to-end API and database testing, including event-driven testing. Mostly, I used it for distributed system testing.

    I integrated a workflow as a core data store within a data pipeline for QA validation. Couchbase Enterprise  acts as my primary NoSQL database for storing JSON documents such as orders and users. The API interacts directly with Couchbase Enterprise for low latency read and write operations. I validate API responses versus database data consistency and data correctness after business operations. For data pipeline validation, I use PySpark to extract data from Couchbase Enterprise for large-scale validation, which is useful in ETL data engineering workflows. I then use data quality automation with Great Expectations where I perform data quality checks such as schema, null, range, and business rules validation. For end-to-end testing, I verify whether all data and subsequent data landed into the target correctly from source to database. I also tested distributed system scenarios including failover, recovery, rebalancing, replication, and load balancing to ensure the cluster responds correctly without any data loss when a node goes down. I then evaluated query performance across these scenarios.

    What is most valuable?

    Couchbase Enterprise offers sub-millisecond response times with built-in memory cache and storage in the storage engine. Rebalancing plus failover are valuable, and the platform supports key-value, multi-model database functionality including key-value support, SQL query, JSON documents, full-text search, and analytics. I can perform relational operations such as joins and aggregations with indexes. Built-in replication, high availability, VBucket system, automatic failover, and cross data replication are all valuable features. There is also mobile edge support and offline sync capability. Enterprise-grade security includes audit logging and compliance with HIPAA and PCI standards. The vector search feature is also a valuable addition.

    In my day-to-day work, I mainly use SQL transactions and SQL queries combined with proper indexing because it helps me perform easy validation and fast debugging. Indexing enables strong data validation and increases performance. Support for joins and aggregation helps in defining relationships across the database, and these are the standout features I use.

    The best features are high availability, failover, replication, VBucket, and XDCR, which stand out in handling failures without impacting the application. Data is always stored with a replica copy. If a node fails, replica VBuckets are promoted automatically with no data loss and minimal service disruption. This gives me strong confidence and is critical for distributed systems, disaster recovery, and geo-distributed applications. For someone working on data validation and distributed systems, this provides confidence that even under failure conditions, the system maintains data integrity and availability. In addition to SQL++ query capabilities, I really value Couchbase Enterprise's built-in high availability and failover mechanism, the way it handles replication and automatic failover.

    For the enterprise, we have faster read and write latency and real-time use cases with fewer bottlenecks. Couchbase Enterprise combined with a database, cache, and query engine helps in faster retrieval of queries and it is a single platform that handles everything. SQL++ query can quickly validate back-end data and debug issues faster. It integrates with PySpark and Great Expectations, so schema validations and data quality rules can be handled much earlier. Built-in failover, replication factor, and failover mechanisms give minimal downtime and high confidence during deployment. Scalability is a major factor as it can scale very easily.

    Couchbase Enterprise has significantly improved performance and enabled real-time data access while simplifying our architecture by combining cache and database capability. It has enhanced data validation and testing efficiency through SQL++ query, and its built-in scalability and high availability have allowed us to grow workload reliability with minimal downtime. The cache layer combined with Couchbase Enterprise database cache plus query layer has reduced infrastructure and maintenance cost by twenty to thirty percent with fewer licenses, fewer servers, and less operational overhead. Faster API response due to in-memory architecture and efficient indexing provides better user experience and higher throughput. Reduced debugging time and issue resolution time by forty to fifty percent. PySpark integrated with Great Expectations has improved automation efficiency and reduced manual effort of database checking. Horizontal scaling has improved deployment and scalability speed. From a cost and efficiency perspective, Couchbase Enterprise has helped reduce infrastructure and operational costs and consolidated multiple systems into a single platform. We saw a two to five times improvement in API response and debugging time reduced to nearly five percent. Automation saved about thirty to forty percent in data validation time.

    What needs improvement?

    Bucket concepts such as bucket, scope, collection, VBucket are very new to users and take time to understand. Better guided onboarding and simplified documentation with real-world examples could help. Index complexity and management including choosing the right index, managing index fragmentation, and memory overhead could be improved. Smarter index recommendations using AI-driven analysis and better visualizations, data lineage, and understanding of data flow could help users understand how things work. RAM quota, index service memory, and data allocation issues can impact performance and could be solved with more automation of resource optimization. Better cost and performance recommendations can be provided.

    Replication lag, failover behavior, and rebalancing issues could benefit from better observability, a more intuitive dashboard, or root cause analysis capability. A dashboard to track licensing and cost would make users aware of their consumption. End-to-end query tracing would be helpful because in real-time projects, creating and dropping indexes through query services and indexing services does not always have obvious performance impacts. Switching between dashboard logs to correlate query latency, index scanning time, and node resource usage takes considerable time.

    During scaling or node replacement, rebalancing takes time and system performance can degrade temporarily. More adaptive and throttled rebalance with minimal impact may help. In addition to using Great Expectations, built-in data quality checks within Couchbase Enterprise would help in identifying end-to-end data quality issues. Error reporting and analysis can be improved significantly, which will help in reducing debug time.

    For how long have I used the solution?

    I have been using the solution for around six to seven years.

    What do I think about the stability of the solution?

    Couchbase Enterprise is stable. This is why we are continuing to work with it and building a connector on top of it. There are no significant issues with Couchbase Enterprise. It is a reliable production environment and a good product.

    What do I think about the scalability of the solution?

    Horizontal scaling has been very good. Even with multi-dimensional query levels, vertical scaling has been efficient and cost optimization has been achieved.

    How was the initial setup?

    I would say the setup is moderately easy. Cluster setup, UI, and basic configuration were straightforward. What was challenging was production-level configuration, index planning, AWS  integration, and the learning curve for the team in scaling operations.

    What other advice do I have?

    Organizations that Couchbase Enterprise is best suited for include medium to high e-commerce companies, streaming services, some financial companies, though banking may not be the primary focus. Mobile-first, SaaS, and microservice-based companies are ideal candidates.

    I will definitely recommend Couchbase Enterprise to others as it handles high performance, scalability, and real-time data handling effectively. I gave this review a rating of eight out of ten.

    Which deployment model are you using for this solution?

    Hybrid Cloud

    If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

    Amazon Web Services (AWS)
    Srijithv Mca

    Flexible queries and fast indexing have transformed how I manage and retrieve customer data

    Reviewed on Mar 27, 2026
    Review from a verified AWS customer

    What is our primary use case?

    My main use case for Couchbase Enterprise  is to store data according to our requirements in our telecom-based company to manage, store, and retrieve information from the database. After two years of using Couchbase Enterprise , I find it very good. Being a NoSQL database, it allows for easy data storage and retrieval. I primarily use Java Spring Boot  and make use of Couchbase Enterprise POM as well.

    A specific example of how Couchbase Enterprise helped me manage and retrieve data efficiently is when I create a customer by gathering all relevant information such as name, email, and phone number, and I utilize the CRUD repository in the Java code to store it in Couchbase Enterprise. I call the save method to store the created records, triggering the API from the backend, which then stores the data in the repository, reflecting my basic flow.

    Regarding my main use case with Couchbase Enterprise, I can share that in the Couchbase Enterprise GUI, I utilize N1QL for searching using meta queries, which is very helpful for running queries. Unlike MongoDB, where writing complex queries is necessary, Couchbase Enterprise allows me to directly write SQL queries to retrieve data easily, and this has been a very good experience.

    What is most valuable?

    The best features Couchbase Enterprise offers in my experience include the indexing part, which I find very beneficial. In the Couchbase Enterprise GUI, creating indexes is straightforward as I have learned from YouTube and the documentation, making it easy. I also appreciate the caching part, so I am not using additional tools like Redis .

    In terms of performance, Couchbase Enterprise is very good and fast to retrieve and manage data, although I have not explored much else.

    Couchbase Enterprise has positively impacted my organization by being a positive point for data management, although I am not certain about specific metrics like productivity or cost savings as I do not have insight into that being an employee.

    What needs improvement?

    Couchbase Enterprise is in a good state, and I have no negative reviews or suggestions for improvements.

    For how long have I used the solution?

    I have been working in my current field for a total of two years, which includes one year of internship and one year of full-time employment.

    What's my experience with pricing, setup cost, and licensing?

    I do not have any thoughts on the pricing, setup cost, and licensing for Couchbase Enterprise as these matters are managed by the DevOps team. I am a developer and only receive credentials and access.

    What other advice do I have?

    My advice for others looking into using Couchbase Enterprise is that it offers a lenient learning curve compared to many databases in the market. It combines features of both MongoDB and SQL, making it easier for developers to work with JSON data and write queries in a straightforward manner using N1QL.

    Which deployment model are you using for this solution?

    Public Cloud

    If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

    Shantanu Deshmukh

    Vendor analytics have become faster and complex migrations run smoothly with readable queries

    Reviewed on Mar 23, 2026
    Review provided by PeerSpot

    What is our primary use case?

    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.

    What is most valuable?

    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.

    What needs improvement?

    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.

    For how long have I used the solution?

    I have been using Couchbase Enterprise for a year.

    Which solution did I use previously and why did I switch?

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

    What other advice do I have?

    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.

    reviewer2810886

    Caching workflows have cut response times and support flexible query-driven data access

    Reviewed on Mar 21, 2026
    Review provided by PeerSpot

    What is our primary use case?

    My main use case for Couchbase Enterprise  is to utilize it for cache, as we have a database as SQL, but we use Couchbase Enterprise  for cache.

    A specific example of how I use Couchbase Enterprise for caching in my workflow is with two components, ARI and Booking. If ARI is calling the database multiple times, that increases the response time. However, in Couchbase Enterprise, we have a document system that stores a particular response in the form of documents and the key, allowing us to find that document using that key. We just search with that key, and once the key is found, it is readily available for any number of times the request hits, resulting in very good response time once we use the cache.

    Couchbase Enterprise also helps us to find and negotiate the time that we use between our calls, and it is very helpful as we can get a visual representation on the UI. We can use a query system to search our documents when needed for searching purposes, and it is a very maintainable thing; it is very light and easy to use.

    What is most valuable?

    In my opinion, the best features Couchbase Enterprise offers are the keys and the queries. While all cache providers can provide cache facilities, the key and the document key that gets made, along with the ability to search with a query for the documents that you have, is a very good thing.

    The querying capabilities help me in my day-to-day work by being very easy. I can write SQL-like queries. For example, if a document key is ABC, I can search directly as SELECT * FROM ABC.Z.Z, and it will print the whole document or the whole list of data from that. It is very easy to use, user-friendly, and I can customize my queries as I like, making them very specific to my company and my team.

    Regarding performance and integration, Couchbase Enterprise performs very well. It is very easy to integrate into components, especially if you are using Java. You just have to integrate a few APIs and dependencies, and the rest depends on the custom integration that you want to do. The extent of customization needed is up to you.

    Couchbase Enterprise has positively impacted my organization by significantly reducing the response time; it was nearly cut to half or below that after we introduced Couchbase Enterprise. When we fetch queries from the database, it is very easy. We also introduced a thirty-minute refresh of the documents, keeping them up to date as the data changes every half hour or every ten minutes, making it very helpful with less response time.

    I can provide specific metrics on the reduction in response time. When we were using database queries, the user API took around one point five to one point eight seconds to fetch all the data. After using Couchbase Enterprise, it takes nearly zero point five seconds.

    What needs improvement?

    Couchbase Enterprise can improve by being a little lighter for use cases as it requires heavy customization. It should be more structured so one can tweak configurations easily. In Couchbase Enterprise, most modifications are necessary, and the boilerplate code is insufficient.

    There is room for improvement in documentation regarding integration. Couchbase Enterprise's documentation is good, but for integration purposes, having better boilerplate code would be very helpful for customization and for new users of Couchbase Enterprise.

    For how long have I used the solution?

    I have been using Couchbase Enterprise for around two years.

    What do I think about the stability of the solution?

    Couchbase Enterprise is very stable in my experience.

    What do I think about the scalability of the solution?

    Couchbase Enterprise does scale very well. You just have to customize it, and there are many options to pick from. The documents they have are very useful, and you can use the customized variables to manage scalability.

    How are customer service and support?

    I have interacted with Couchbase Enterprise's customer support team, which was very helpful during a Cloudflare  attack that affected our servers. They provided a point of contact for our India team and did everything to resolve our issue, helping us recover lost data effectively.

    Which solution did I use previously and why did I switch?

    We did not previously use a different solution; we were looking for caching solutions and comparing Couchbase Enterprise with Redis  and others, eventually settling on Couchbase Enterprise.

    How was the initial setup?

    We purchased Couchbase Enterprise through the Azure Marketplace .

    My experience with pricing, setup cost, and licensing was good because we had an agent from our company to assist us with Azure Marketplace , and the process was very smooth.

    What about the implementation team?

    Before choosing Couchbase Enterprise, we specifically evaluated Couchbase Enterprise and Redis . We chose Couchbase Enterprise because it was price convenient and allowed for more customization in document keys and various adjustments. Redis was more constrained, lacking a UI for visualization, which did not fit our requirements.

    What was our ROI?

    We have seen a return on investment because there was significant money saved. We faced many troubles with response times, which means money lost. After starting to use Couchbase Enterprise, we cut the response time to below half, and we observed a twenty to thirty-five percent improvement in pricing, representing overall value for money.

    What's my experience with pricing, setup cost, and licensing?

    We purchased Couchbase Enterprise through the Azure Marketplace.

    My experience with pricing, setup cost, and licensing was good because we had an agent from our company to assist us with Azure Marketplace, and the process was very smooth.

    Which other solutions did I evaluate?

    Before choosing Couchbase Enterprise, we specifically evaluated Couchbase Enterprise and Redis. We chose Couchbase Enterprise because it was price convenient and allowed for more customization in document keys and various adjustments. Redis was more constrained, lacking a UI for visualization, which did not fit our requirements.

    What other advice do I have?

    My advice for others looking into using Couchbase Enterprise is to use it; it is very good and offers a lot of customization options and a better UI than other caches. Once you start using this product, you will see it help decrease response time and increase API capabilities.

    For those considering Couchbase Enterprise, I encourage you to try it out for study or evaluation purposes. You will find a proper UI, a solid setup, and comprehensive documentation available online, making it very helpful to get started. Using Couchbase Enterprise will lead to improvements in your applications. I would rate this product an eight out of ten. Thank you.

    reviewer4089163

    Session management has simplified user profiling and currently reduces time spent on analytics

    Reviewed on Mar 20, 2026
    Review provided by PeerSpot

    What is our primary use case?

    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.

    What is most valuable?

    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.

    What needs improvement?

    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.

    For how long have I used the solution?

    I have been using Couchbase Enterprise for almost ten years.

    What do I think about the stability of the solution?

    Couchbase Enterprise is stable.

    What do I think about the scalability of the solution?

    The scalability of Couchbase Enterprise is good.

    How are customer service and support?

    The customer support for Couchbase Enterprise is great.

    How was the initial setup?

    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.

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