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Amazon DynamoDB vs Amazon DocumentDB: What are the differences?

Amazon DynamoDB: Fully managed NoSQL database service. With it , 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; Amazon DocumentDB: Fast, scalable, highly available MongoDB-compatible database service. Amazon DocumentDB is a non-relational database service designed from the ground-up to give you the performance, scalability, and availability you need when operating mission-critical MongoDB workloads at scale. In Amazon DocumentDB, the storage and compute are decoupled, allowing each to scale independently, and you can increase the read capacity to millions of requests per second by adding up to 15 low latency read replicas in minutes, regardless of the size of your data.

Amazon DynamoDB and Amazon DocumentDB can be primarily classified 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
  • Fully Distributed, Shared Nothing Architecture

On the other hand, Amazon DocumentDB provides the following key features:

  • MongoDB-compatible
  • Fully managed
  • Performance at scale
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Pros of Amazon DocumentDB
Pros of Amazon DynamoDB
    Be the first to leave a pro
    • 62
      Predictable performance and cost
    • 56
      Scalable
    • 35
      Native JSON Support
    • 21
      AWS Free Tier
    • 7
      Fast
    • 3
      No sql
    • 3
      To store data
    • 2
      Serverless
    • 2
      No Stored procedures is GOOD
    • 1
      ORM with DynamoDBMapper
    • 1
      Elastic Scalability using on-demand mode
    • 1
      Elastic Scalability using autoscaling
    • 1
      DynamoDB Stream

    Sign up to add or upvote prosMake informed product decisions

    Cons of Amazon DocumentDB
    Cons of Amazon DynamoDB
      Be the first to leave a con
      • 4
        Only sequential access for paginate data
      • 1
        Scaling
      • 1
        Document Limit Size

      Sign up to add or upvote consMake informed product decisions

      What is Amazon DocumentDB?

      Amazon DocumentDB is a non-relational database service designed from the ground-up to give you the performance, scalability, and availability you need when operating mission-critical MongoDB workloads at scale. In Amazon DocumentDB, the storage and compute are decoupled, allowing each to scale independently, and you can increase the read capacity to millions of requests per second by adding up to 15 low latency read replicas in minutes, regardless of the size of your data.

      What is Amazon DynamoDB?

      With it , 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.

      Need advice about which tool to choose?Ask the StackShare community!

      What companies use Amazon DocumentDB?
      What companies use Amazon DynamoDB?
      See which teams inside your own company are using Amazon DocumentDB or Amazon DynamoDB.
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      What tools integrate with Amazon DocumentDB?
      What tools integrate with Amazon DynamoDB?

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      What are some alternatives to Amazon DocumentDB and Amazon DynamoDB?
      MongoDB
      MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
      MongoDB Atlas
      MongoDB Atlas is a global cloud database service built and run by the team behind MongoDB. Enjoy the flexibility and scalability of a document database, with the ease and automation of a fully managed service on your preferred cloud.
      Elasticsearch
      Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
      Atlas
      Atlas is one foundation to manage and provide visibility to your servers, containers, VMs, configuration management, service discovery, and additional operations services.
      Cloud Firestore
      Cloud Firestore is a NoSQL document database that lets you easily store, sync, and query data for your mobile and web apps - at global scale.
      See all alternatives