We compared Amazon DynamoDB and Microsoft Azure Cosmos DB based on our user's reviews across parameters. After reading all of the collected data, you can find our conclusion below.
Amazon DynamoDB and Microsoft Azure Cosmos DB, while both providing robust cloud database solutions, exhibit distinct features tailored to diverse user needs. DynamoDB, embedded within the AWS ecosystem, excels in managed scalability, security, and high availability but faces criticism over cost predictability and the steep learning curve for new users. Azure Cosmos DB stands out with its multi-model support and global distribution, offering flexibility and performance optimization across geographically dispersed areas. However, it also presents challenges with its complex pricing structure and steep learning curve. Both platforms indicate potential areas for improvement in cost transparency and user-friendly documentation, but they also maintain solid reputations for enhancing data management through their respective unique strengths.
The summary above is based on 53 interviews we conducted recently with Amazon DynamoDB and Microsoft Azure Cosmos DB users. To access the review's full transcripts, download our report.
"Offers a vital query-handling feature"
"Speed is the most valuable feature. The speed to store and retrieve data from it."
"We directly pass the JSON value to Amazon DynamoDB, which is why Amazon DynamoDB is faster than relational databases."
"It offers quick performance and rapid data retrieval, often providing limited data initially but scaling up to fulfill larger demands seamlessly."
"The most valuable feature of this solution is the non-relational database."
"The best feature is NoSQL."
"Never used the support. I got all the information from the documentation."
"Amazon DynamoDB is powerful and fast. Its performance is good."
"Since it's a managed service, Azure backend handles scalability. From a user's perspective, we don't need to worry about scalability."
"Cosmos is a PaaS, so you don't need to worry about infrastructure and hosting. It has various APIs that allow it to integrate with other solutions. For example, we are using a MongoDB-compatible API for customers, which makes it easier for developers on the team who previously used MongoDB or are accustomed to the old document storage paradigm."
"Cosmos DB is stable and easy to use."
"The product has a lot of useful features that are there and ready to use, it's also very easy to use."
"Cosmos DB makes life easier because if we want to use Mongo-type data, or Cassandra-type data, or maybe even just a simple cable storage-type data, then graph, there are multiple ways to do this."
"The solution is stable."
"It is non-SQL and helps to manage and manipulate data from the coding, rather than direct data and complex queries."
"One of the nice features is the ability to auto-scale"
"The response time for data queries should be less than a second"
"The solution could be cheaper."
"I'd like to see better integration with Cognito. It has the integration, but I'd like to see a little more ease of setup. If you have multiple customers and you want the database to enforce who can see what, you can treat DynamoDB so that each row has permissions. You can set this up, but it's a little more of a science project to make Cognito and DynamoDB work well to do protection of individual rows. So I'd like that to be more wizard or easy to set up."
"They could provide more information or training programs to deliver knowledge to the engineers about the components of relational databases similar to popular vendors."
"It would be nice to have some AI features in DynamoDB."
"Data integrity across availability zones would be a valuable addition. Currently, DynamoDB provides eventual consistency across availability zones, but strong consistency would be beneficial for certain use cases."
"Sometimes when we query through the UI, it takes a long time to get the results."
"Maybe the documentation could be improved a bit. Sometimes, it's a little confusing, and people can easily be mistaken about DynamoDB."
"There is room for improvement in terms of stability."
"Microsoft Azure Cosmos DB's performance could be better. In large volumes of documents, the querying process becomes slow and complicated."
"The solution’s pricing could be improved."
"I would like to see Cosmos DB introduce a feature that would convert machine language to human-readable queries."
"The initial setup was difficult."
"At this stage, we would like more enterprise support. We use MongoDB a lot, and we're trying to get rid of MongoDB. So, I would like to see more features in the Cosmos DB API for MongoDB space."
"The integration of the on-premise solution with the cloud can be difficult sometimes."
"It is not as easy to use as DynamoDB."
Amazon DynamoDB is ranked 2nd in Managed NoSQL Databases with 31 reviews while Microsoft Azure Cosmos DB is ranked 1st in Managed NoSQL Databases with 38 reviews. Amazon DynamoDB is rated 8.4, while Microsoft Azure Cosmos DB is rated 8.0. The top reviewer of Amazon DynamoDB writes "Manages our contact center dynamically and allows us to store multiple data attributes in tables". On the other hand, the top reviewer of Microsoft Azure Cosmos DB writes "Removes bottlenecks related to databases in our application and works quickly because of reference keys". Amazon DynamoDB is most compared with Amazon DocumentDB, Google Cloud Bigtable, Amazon Neptune, Amazon Timestream and Oracle NoSQL Database Cloud, whereas Microsoft Azure Cosmos DB is most compared with Amazon Neptune, Google Cloud Bigtable, Neo4j AuraDB, Amazon DocumentDB and Amazon Timestream. See our Amazon DynamoDB vs. Microsoft Azure Cosmos DB report.
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We monitor all Managed NoSQL Databases reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.