HA clusters enable 99.995% uptime SLA regardless of where MongoDB is hosted. Unlike Cassandra instance provisioning, DynamoDB provisioning is not fixed, and it’s through auto-scaling that helps to put a check on the database resources. This is a BIG plus. AWS Reliability – A Core Pillar of Your Architecture, Scalability in Cloud Computing & Why We Love AWS, 28 AWS Launches Announced by Andy Jassy at re:Invent 2020, AWS Control Tower: Everything you Need To Know, Webinar – Optimising Availability & Performance Of EdTech Applications With AWS, AWS Identity and Access Management Best Practises, AWS Service Level Agreement – What you need to know, Easier horizontal scaling to clusters of servers. Fast analytics queries can be achieved with on-demand materialized views. The pros and cons of a database engine for your business will likely depend upon your dev team and the applications you use. But DynamoDB is only available in AWS and nowhere else. If you're already using the AWS stack and you need a NoSQL database, then DynamoDB is a no-brainer. A NoSQL database system or DynamoDB are actually rather fitting for your use case because of two things you mentioned: always reading by key, and storing the actual data in JSON format which allows for semi-structured, unstructured, and varying structured data. It forces you to think about designing your data model up front in a way that will scale. It will depend largely on the long term cloud strategy of your business, plus the specific requirements of your application. DynamoDB is schemaless. Ever uploaded a photo to social media, only to find you can’t view it for a while? On the other hand, DynamoDB integrates with Elastic Map Reduce and reduces the complexity of analyzing unstructured data. It’s a more common practice to assign certain permissions and access keys to users than go with user roles. In a few hours, you can have a Slack bot or a GitHub webhook handler. The databases are deploying and delivering high-scalable, cloud-performance, and addressing significant insufficiencies in conventional RDBMS. NoSQL data might not relate to each other, but SQL does. Each of course has their advantages and disadvantages – your choice is likely to be guided by your long term cloud strategy and the specific requirements of your application. The great news is that companies and teams can buy managed Cassandra clusters also. DynamoDB can only be accessed via the AWS SDK, and access is secured by AWS IAM (Identity and Access Management). Undoubtedly, in the era of NoSQL databases, MongoDB and Amazon DynamoDB are gaining momentum. https://www.logicata.com/blog/aws-dynamodb-vs-mongodb-a-nosql-comparison Due to a vast community and support for clusters spanning multiple data centers and cloud, this ensures a zero point of failure in most cases. Relaxed vs Strong consistency. AWS Dynamo DB is available on the AWS Free Tier, meaning users can experiment with building their first DynamoDB tables at no cost. Users can get started with DynamoDB with virtually no upfront cost. NoSQL databases are often used in big data and real-time web applications. Our founder hand picks the most interesting, the best tips and most relevant technical details, strips the nonsense and delivers it to your inbox once a week. AWS DynamoDB is a fully managed AWS service, so you can obviously only run it in the AWS cloud – there is no on-premises option. This allows applications … Managed in-memory caching enables microsecond read times and supports peaks of 20+ million requests per second. several NoSQL solutions in the market today and choosing the right one for your use case can be difficult. You can find a full description on Wikipedia, but let me summarize here. Amazon DynamoDB is a document and key-value database. Amazon DynamoDB offers multiple advantages over other NoSQLdatabase management systems such as Apache Cassandra and MongoDB. MongoDB describe Atlas as the ‘easiest way to run MongoDB’. Cassandra allows applications to access the data using multiple attributes. DynamoDB, on the other hand, uses a shift-left model of scalability. People don’t like being woken up in the middle of the night. Once you are ready to make the switch, you simply need to update the connection string in your application code to point to the new MongoDB Atlas database. Of the many NoSQL databases out there, perhaps DynamoDB is the closest to Fauna, where both databases share a similar value proposition as "serverless databases". Given its open-source nature, it can run in any cloud or on-premise environment. If the application is of unstructured data, DynamoDB would be a better choice. ... On the other hand, HBase can be a very good solution for write-heavy applications and enormous amounts of records. Both of these NoSQL databases can deliver performance and high availability at global scale. Amazon offer migration guides to migrate to DynamoDB from other database engines including MongoDB, Cassandra, MySQL, plus they offer the Amazon Database Migration Service tool to simplify migrating to Dynamo DB. This paper compares two popular NoSQL data stores—Amazon DynamoDB, a fully managed NoSQL cloud database service, and Apache HBase, an open-source, column-oriented, distributed big data store. Cassandra and DynamoDB both origin from the same paper: Dynamo: Amazon’s Highly Available Key-value store. It's a fully managed, multi-region, multi-active, durable database with built-in security, backup and restore, and in-memory caching for internet-scale applications. This is common across all NoSQL databases. Setting up Dynamo was a breeze. Data access is role-based, the smallest level of granularity is a row and, besides that, Cassandra offers client-to-node and inter-node encryption. 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