Need advice about which tool to choose?Ask the StackShare community!
Amazon DynamoDB vs Cloudant: What are the differences?
What is Amazon DynamoDB? Fully managed NoSQL database service. All data items are stored on Solid State Drives (SSDs), and are replicated across 3 Availability Zones for high availability and durability. With DynamoDB, you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.
What is Cloudant? Distributed database-as-a-service (DBaaS) for web & mobile apps. Cloudant’s distributed database as a service (DBaaS) allows developers of fast-growing web and mobile apps to focus on building and improving their products, instead of worrying about scaling and managing databases on their own.
Amazon DynamoDB and Cloudant can be categorized as "NoSQL Database as a Service" tools.
Some of the features offered by Amazon DynamoDB are:
- Automated Storage Scaling – There is no limit to the amount of data you can store in a DynamoDB table, and the service automatically allocates more storage, as you store more data using the DynamoDB write APIs.
- Provisioned Throughput – When creating a table, simply specify how much request capacity you require. DynamoDB allocates dedicated resources to your table to meet your performance requirements, and automatically partitions data over a sufficient number of servers to meet your request capacity. If your throughput requirements change, simply update your table's request capacity using the AWS Management Console or the Amazon DynamoDB APIs. You are still able to achieve your prior throughput levels while scaling is underway.
- Fully Distributed, Shared Nothing Architecture – Amazon DynamoDB scales horizontally and can seamlessly scale a single table over hundreds of servers.
On the other hand, Cloudant provides the following key features:
- Managed- Cloudant's big data experts monitor your data 24/7 to ensure its high availability and safety.
- Distributed Multi-Master Database- All read and write transactions can be synced across Cloudant's global data network without global locks, providing true high availability of your data.
- Geo-load Balancing- To keep latency low, our geo-load balancing infrastructure routes requests to the copies of the data that are geographically closest to the requestor.
"Predictable performance and cost" is the top reason why over 53 developers like Amazon DynamoDB, while over 8 developers mention "JSON" as the leading cause for choosing Cloudant.
We are building a social media app, where users will post images, like their post, and make friends based on their interest. We are currently using Cloud Firestore and Firebase Realtime Database. We are looking for another database like Amazon DynamoDB; how much this decision can be efficient in terms of pricing and overhead?
Hi, Akash,
I wouldn't make this decision without lots more information. Cloud Firestore has a much richer metamodel (document-oriented) than Dynamo (key-value), and Dynamo seems to be particularly restrictive. That is why it is so fast. There are many needs in most applications to get lightning access to the members of a set, one set at a time. Dynamo DB is a great choice. But, social media applications generally need to be able to make long traverses across a graph. While you can make almost any metamodel act like another one, with your own custom layers on top of it, or just by writing a lot more code, it's a long way around to do that with simple key-value sets. It's hard enough to traverse across networks of collections in a document-oriented database. So, if you are moving, I think a graph-oriented database like Amazon Neptune, or, if you might want built-in reasoning, Allegro or Ontotext, would take the least programming, which is where the most cost and bugs can be avoided. Also, managed systems are also less costly in terms of people's time and system errors. It's easier to measure the costs of managed systems, so they are often seen as more costly.
CouchDB has proven us to be a reliable multi-master NoSQL JSON database built natively for the web.
We decided to use it over alternatives such as Firebase due topology, costs and frontend architecture.
Thanks to CouchDB we are now a frontend first CRM platform. We are capable of delivering and leveraging our frontend code to build most of our new functionalities directly within the frontend which we enrich through backend sidecars connected to each Parrot and each CouchDB.