Amazon DynamoDB is a cloud-native, NoSQL, serverless database service.
$0
capacity unit per hour
Couchbase Server
Score 8.7 out of 10
N/A
Couchbase Server is a cloud-native, distributed database that fuses the strengths of relational databases such as SQL and ACID transactions with JSON flexibility and scale that defines NoSQL. It is available as a service in commercial clouds and supports hybrid and private cloud deployments.
N/A
Pricing
Amazon DynamoDB
Couchbase Server
Editions & Modules
Provisioned - Read Operation
$0.00013
capacity unit per hour
Provisioned - Write Operation
$0.00065
capacity unit per hour
Provisioned - Global Tables
$0.000975
per Read Capacity
On-Demand Streams
$0.02
per 100,000 read operations
Provisioned - Streams
$0.02
per 100,000 read operations
On-Demand Data Requests Outside AWS Regions
$0.09
per GB
Provisioned - Data Requests Outside AWS Regions
$0.09
per GB
On-Demand Snapshot
$0.10
per GB per month
Provisioned - Snapshot
$0.10
per GB per month
On-Demand Restoring a Backup
$0.15
per GB
Provisioned - Restoring a Backup
$0.15
per GB
On-Demand Point-in-Time Recovery
$0.20
per GB per month
Provisioned - Point-in-Time Recovery
$0.20
per GB per month
On-Demand Read Operation
$0.25
per million requests
On-Demand Data Stored
$0.25
per GB per month
Provisioned - Data Stored
$0.25
per GB per month
On-Demand - Write Operation
$1.25
per million requests
On-Demand Global Tables
$1.875
per million write operations replicated
No answers on this topic
Offerings
Pricing Offerings
Amazon DynamoDB
Couchbase Server
Free Trial
No
Yes
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
Optional
Additional Details
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More Pricing Information
Community Pulse
Amazon DynamoDB
Couchbase Server
Considered Both Products
Amazon DynamoDB
Verified User
Anonymous
Chose Amazon DynamoDB
For our use case, we needed a noSQL that would work with AWS Lambdas of specific parts of the internal web applications. We optimized billing and uses , diversified databases for various parts; so it’s not very expensive.
Other all SQL Databases are based on the traditional Schema Structure and Amazon DynamoDB is NoSQL so you don't need to generate the SQL Schemas. You can store the data whatever you want, whenever you want. You can store data in structured or non-structured any way you want. If …
Performance at high scales is better and the cost at high scales is less. If one has a ton of data generated and has to work their way through it, I think Amazon DynamoDB should the go-to database. There are no compromises when it comes to performance at a huge scale. With any …
MongoDB was basically the first approach we used but because there was concern that some data may miss we were reluctant to use it. Oracle Database and SQL Server was our second approach but it was throttling so in last we tested out Amazon DynamoDB and it met our requirement.
The Amazon Web Services managed Amazon DynamoDB has excellent features which makes it stand out from all the others in market right now. The management ease it offers is far superior than its competitors and on top of that the on-demand pricing model is an advantage which works …
MongoDB has some performance issues and can get corrupted from time to time and has needed to be rebuilt. We have not had that experience while using DynamoDB.
Amazon DynamoDB supports larger throughput, with better SLA, also, we are considering unstructured data, so Amazon DynamoDB has become the final decision
The only thing that can be compared to DynamoDB from the selected services can be Aurora. It is just that we use Aurora for High-Performance requirements as it can be 6 times faster than normal RDS DB. Both of them have served as well in the required scenario and we are very …
DynamoDB offers strong consistency, more fine-grained control over read and write capacities, and integrates seamlessly with other AWS services. DynamoDB is designed for horizontal scalability and high throughput, making it a better choice for applications with rapidly changing …
AWS handles hardware provisioning, data recovery, fault tolerance, patching, and database upgrades for DynamoDB since it is a fully managed database service. Businesses can then concentrate on other aspects of their operations, including product development or customer service, …
The automation is much more subtle and it performs way better for internet-scale applications. No matter the number of connections, the performance doesn't dip even a bit.
DynamoDB's scalability is more automated and effortless, making it easier to handle rapid growth. Other tools require more manual configuration while DynamoDB simplifies database administration. Also, DynamoDB provides strong consistency while other tools like MongoDB and …
We are always assembling our solutions on AWS and DynamoDB is a better fit for us because of its simplicity. DynamoDB has its ow sets of triggers that make this an integrated solution on AWS. Besides, we wanted to use a key-value solution for our simple edge DB, and we didn't …
DynamoDB is slightly different than both the above-stated DBs, with RDS being a relational database and Redshift being a data warehouse used for heavier jobs and analytics and vast data. DynamoDB lies in between both, with it being a no SQL base that can relatively store …
Lesser flexibility but better performance, and more predictable development support are the key points where Amazon DynamoDB comes out on top, when compared to MongoDB.
Mongo services are outside of our Vpc and are on a different network. Since most of our infra is on AWS, dynamo by AWS was a natural choice. Most of our engineers are familiar with AWS sdk and the console so that brought in a much smaller learning curve for our engineering team
The project we are developing with Couchbase, was very inconsistent for few years of the beginning. We had to change data model multiple times. We knew this before starting the project. So we had to choose a NoSQL solution. We also wanted a syncing solution. After some research …
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.
At the time, Couchbase seemed the most mature of the NoSQL products and would allow us to achieve the goal of improving data access times for our products and services, giving the most benefit to our customers. MySQL was starting to be the bottleneck in our system performance …
Easy to deploy and manage. Clustering and replication is fairly simple and straightforward. According to developers, Couchbase scored higher points compared to the other products that we evaluated.
The Apache Cassandra was one type of product used in our company for a couple of use-cases. The Aerospike is something we [analyzed] not so long time ago as an interesting alternative, due to its performance characteristics. The Oracle Coherence was and is still being used for …
Single console for managing multi-cluster and multi-cloud deployment options and [the] ability to secure and isolate database information in a secure environment to prevent undefined access is great. Analyzing and delivering information and fast access and processing data …
Experience with DataStax Cassandra was seamless, but the cost and effort to support it was not justified. Also commercial process experience with Couchbase was much better. ActiveSpaces is a good technology for big TIBCO shop, but keeping with the lifecycle of it is not easy. I …
A strategic company, upcoming products, enhanced concepts. Couchbase is a single platform offering many different smaller products together viz Full-Text Search, Analytics, Eventing, Indexing, Querying, Integration with other products.
I'm not qualified enough to make a meaningful comparison, but 2 years after, I hear regularly about issues on Mongo from the other teams, especially on the SRE side. On our side, not much to say, except that it works. Ram, CPU, disk behave like expected. Same for bandwidth. …
It is useful use-case by use-case. For our use case, it was the best and easiest option for the integration as well as development side. It is serverless so no need of deployment and maintenance hustle. It is easy to scale up due to the same functionality. Supports AWS Security features and just a click away for enabling it so security is good.
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.
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.
It's core to our business, we couldn't survive without it. We use it to drive everything from FTP logins to processing stories and delivering them to clients. It's reliable and easy to query from all of our pipeline services. Integration with things like AWS Lambda makes it easy to trigger events and run code whenever something changes in the database.
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
Functionally, DynamoDB has the features needed to use it. The interface is not as easy to use, which impacts its usability. Being familiar with AWS in general is helpful in understanding the interface, however it would be better if the interface more closely aligned with traditional tools for managing datastores.
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.
While the actual performance of DynamoDB can vary based on workload and region, it is generally highly responsive and well-regarded for delivering low-latency access to data, making it a strong choice for applications with stringent performance requirements. Organizations often choose DynamoDB for its ability to provide a reliable and performant database service, particularly when combined with effective application design and optimization.
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.
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.
For our use case, we needed a noSQL that would work with AWS Lambdas of specific parts of the internal web applications. We optimized billing and uses , diversified databases for various parts; so it’s not very expensive.
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.
I have taken one point away due to its size limits. In case the application requires queries, it becomes really complicated to read and write data. When it comes to extremely large data sets such as the case in my company, a third-party logistics company, where huge amount of data is generated on a daily basis, even though the scalability is good, it becomes difficult to manage all the data due to limits.
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
Businesses may only pay for the services they actually use thanks to DynamoDB's usage-based pricing approach.
AWS handles hardware provisioning, data recovery, fault tolerance, patching, and database upgrades for DynamoDB since it is a fully managed database service.
DynamoDB differs from conventional relational databases in terms of its data model, which might be difficult for developers accustomed to dealing with SQL-based systems.
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.