We performed a comparison between Amazon DynamoDB and Amazon Neptune based on real PeerSpot user reviews.
Find out what your peers are saying about Microsoft, Amazon Web Services (AWS), Google and others in Managed NoSQL Databases."The technical support team is always available to help us."
"The best feature of the solution is that it is a NoSQL database."
"Speed is the most valuable feature. The speed to store and retrieve data from it."
"Its scalability is really good. I can go up to a petabyte of data. It is more of an on-demand use case. I can go from 100 MB to 1 PB if I want, which is very good. Most of the other databases would want you to stick to a specific data allocation. Its subscription cost is lower than similar databases offered by other vendors."
"Storing is a valuable feature. We can store as an entire object rather than the traditional structure of the data."
"It is a NoSQL product."
"It offers quick performance and rapid data retrieval, often providing limited data initially but scaling up to fulfill larger demands seamlessly."
"Amazon DynamoDB is a fully managed service by AWS, and it is designed to provide fast and predictable performance."
"Relational databases are never good at identifying patterns in graphs or other similar relationships, whereas Amazon Neptune is."
"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."
"The solution's interface is the biggest challenge because if you want to access DynamoDB, you need an AWS account."
"If the database is kept running continuously, extra costs will be incurred. This particular area needs enhancement."
"The pricing for larger databases is higher."
"Amazon DynamoDB could improve by being more robust, having a better user interface and data management. Additionally, there is some limited functionality compared to other solutions, such as MongoDB."
"Having an import option, whether through browsing or local file uploads, would significantly improve the efficiency of data migration, enabling users to swiftly transfer large volumes of data into DynamoDB."
"Currently, there is no option for a scheduled refresh in this solution. We want the data to be populated into DynamoDB on a timely basis. Currently, you have to go to the DynamoDB table and hit the refresh button to populate it with the new data. If you have connected DynamoDB to a BI application for creating visualizations with charts, graphs, or other things, you would want it to get updated as per the schedule so that you have updated visualizations in your BI application."
"The design patterns and the documentation for this solution could be improved. In a future release, we would like to see an improvement of the data push options as we sometimes experience blockers when moving data."
"Amazon Neptune could improve by spreading more awareness for others to have an understanding of the solution because the technology is fairly new. The developer community and larger community do not understand it yet."
Earn 20 points
Amazon DynamoDB is ranked 2nd in Managed NoSQL Databases with 26 reviews while Amazon Neptune is ranked 4th in Managed NoSQL Databases. Amazon DynamoDB is rated 8.4, while Amazon Neptune is rated 9.0. The top reviewer of Amazon DynamoDB writes "A 10/10 solution with effective transaction-based pricing and stable millisecond response time". On the other hand, the top reviewer of Amazon Neptune writes "Useful pattern identification, price well, and straightforward implementation". Amazon DynamoDB is most compared with Amazon DocumentDB, Google Cloud Bigtable, Microsoft Azure Cosmos DB, Amazon Timestream and Oracle NoSQL Database Cloud, whereas Amazon Neptune is most compared with Microsoft Azure Cosmos DB, Neo4j AuraDB, Amazon Timestream and Amazon DocumentDB.
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