Amazon DynamoDB is a cloud-native, NoSQL, serverless database service.
$0
capacity unit per hour
CouchDB
Score 6.0 out of 10
N/A
Apache CouchDB is an HTTP + JSON document database with Map Reduce views and bi-directional replication. The Couch Replication Protocol is implemented in a variety of projects and products that span computing environments from globally distributed server-clusters, over mobile phones to web browsers.
N/A
Pricing
Amazon DynamoDB
Apache CouchDB
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
CouchDB
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Amazon DynamoDB
Apache CouchDB
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
Open Source, and freely able to install it on any OS you desire (the big 3, anyways) CouchDB was selected for that, it's early-adoption of JSON and its mobile-friendly environment. Also, I have used it off and on in various non-professional projects, and it was really one of …
Compared to MongoDB, CouchDB's Map-Reduce paradigm poses a steeper learning curve for SQL users. However, CouchDB's master-master replication is an advantage of implementing a load-balanced solution. Even though, currently, CouchDB has strong community support, as an open …
MongoDB and CouchDB are both document stores, but their concurrency models and ability to scale are very different. MongoDB cannot replicate / shard over unreliable links and network partitions have been the cause of data loss in the past. MongoDB has an easier query language …
It has been 5+ years since we chose CouchDB. We looked an MongoDB, Cassandra, and probably some others. At the end of the day, the performance, power potential, and simplicity of CouchDB made it a simple choice for our needs. No one should use just because we did. As I said …
S3 blew this out of the water, we can get over 30 files a second, almost no failures, auto backed up, don't need our own server, and a much simpler interface with PHP Laravel.
We looked at MongoDB and Firebase. MongoDB gives us the best working db engine with a very intuitive design. However, it does not work as well offline. Firebase was extremely hard to create searching and indexing. Using a third-party to search didn't work for us or at least it …
I have briefly used MongoDB in other products, and it proved that it had better integration capabilities with Ruby on Rails and node.js software platforms, more than CouchDB. But I never had the chance to actually replace CouchDB with MongoDB in the current product to see what …
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.
It's good as a general JSON document store and basic map/reduce system. For more specialized tasks like message queuing, graph traversal, streaming metrics aggregation, or arbitrary table joins, I'd recommend another database.
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.
As a highly distributed database system, CouchDB naturally has strong high availability with traffic load-balancing capability. It is also easy to scale and replicate data in a cluster for redundancy. However, there is still some room for query performance improvement in the future.
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.
Couchdb is very simple to use and the features are also reduced but well implemented. In order to use it the way its designed, the ui is adequate and easy. Of course, there are some other task that can't be performed through the admin ui but the minimalistic design allows you to use external libraries to develop custom scripts
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.
it support is minimal also hw requirements. Also for development, we can have databases replicated everywhere and the replication is automagical. once you set up the security and the rules for replication, you are ready to go. The absence of a model let you build your app the way you want it
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.
Open Source, and freely able to install it on any OS you desire (the big 3, anyways) CouchDB was selected for that, it's early-adoption of JSON and its mobile-friendly environment. Also, I have used it off and on in various non-professional projects, and it was really one of the first exposure to databases in my career
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.
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.
Biggest impact on our business has been that CouchDB has been pretty invisible from a cost or issues perspective. It just works.
We use the Apache releases, so it's free. Of course there is a cost to "free" - we have invested time to become fluent in using and understanding CouchDB. But we feel the investment was well worth the effort and we have a solid, fundamental technology to our products that "just works".
There are some things we do - SaaS vs self-hosting - that have probably been kept simple by using CouchDB. Overall, we are extremely happy with CouchDB.