Compare Couchbase to DynamoDB™

DynamoDB

In general, DynamoDB becomes more expensive at scale because its pricing is linear. DynamoDB writes are also expensive, which means workloads with higher write percentages will be more costly. Datasets with larger item sizes also tend to cost more.

Because DynamoDB pricing is based on throughput, it takes an objective third-party performance test focused on pricing to get an accurate price comparison. It would be extremely difficult to obtain a reliable Couchbase cost comparison without Couchbase throughput data points at various Amazon EC2 instance sizes, cluster sizes, and read/write ratios.

Couchbase

With Couchbase Capella, you simply buy a license and support contract for each database server you need today, and buy more (or draw down) node capacity as needed. Couchbase will automatically rebalance the workload.

DynamoDB

DynamoDB is inseparable from the Amazon Web Services (AWS) platform. On the upside, you get tight integration between DynamoDB and other AWS tools, but at the price of zero portability.

No other vendor runs the AWS proprietary database model. Moving to a different cloud service provider requires extensive re-architecting of your database structure and operations.

In practice, you're stuck with Amazon and AWS for the long run once you commit your data management to a DynamoDB database.

Couchbase

You can install Couchbase on your own bare metal or virtual server, and nearly every cloud computing platform – including AWS – offers a supported drop-in Couchbase installation.

That means Couchbase users on AWS have easy access to the same supporting tools and virtual infrastructure that DynamoDB absolutely depends on.

Furthermore, Couchbase Capella is built for multicloud and hybrid environments, ensuring that enterprise customers can move their applications to and from any cloud.

DynamoDB

Data can be spread across many partitions in DynamoDB. AWS manages the scaling in the background, creating more partitions and shards as needed.

This sounds good, but can lead to performance issues when the database grows. Automatically generated partitions are organized by hand-picked data keys, and a poor choice triggers unbalanced partitions where data needs to be streamed from one unit to another. The result is serious performance penalties.

Couchbase

Couchbase was built for extreme performance from the ground up. Data is sharded automatically to create balanced partitions while a built-in caching layer improves performance at scale.

Global indexing lets developers separate the data partitioning from the access patterns, providing low-latency access to important queries no matter how large the data grows.

An intelligent routing system provides single-network-hop access to data from the application. The last thing you want is a performance penalty for complying with regulations such as GDPR that require data to be domiciled in its country of origin.

DynamoDB

While customers can build mobile applications with DynamoDB, they’ll find that the capabilities needed to ensure 100% uptime, reliability, and speedy app responses are not there.

DynamoDB has no embeddable mobile/IoT database, which is critical to ensure that even when the network is slow or unavailable, users can continue to use the application. Also, there is no support for peer-to-peer syncing between devices, which builds in redundancy and helps give users the most up-to-date information even when they’re not online.

Mobile apps built with DynamoDB are dependent on the internet, which could put you in a risky situation and lead to frustrated end users.

Couchbase

Capella App Services securely sync data from regional availability zones to edge devices, allowing you to store data in offline mode and to query, search, and analyze data at any time, regardless of internet connectivity and speed. Your applications are guaranteed to be always fast and always on.

Couchbase provides Couchbase Lite, an embedded NoSQL JSON document database with no schema and no data migration requirements. These characteristics vastly reduce the complexity of your app, especially as the data model changes naturally over time with the evolution of the app.