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Amazon DocumentDB

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Amazon DocumentDB vs MongoDB Atlas: What are the differences?

Introduction

Amazon DocumentDB and MongoDB Atlas are both managed database services that provide cloud-based hosting for MongoDB databases. While they share certain similarities, there are several key differences between the two platforms.

  1. Pricing Model: Amazon DocumentDB uses a pay-as-you-go pricing model, where users are charged based on the resources consumed. In contrast, MongoDB Atlas offers a flexible pricing structure with options for both pay-as-you-go and dedicated clusters. Users can choose the pricing plan that aligns with their specific needs and budget.

  2. Scalability: MongoDB Atlas allows for seamless scalability with automatic sharding and the ability to scale both vertically and horizontally. On the other hand, Amazon DocumentDB currently does not support horizontal scaling, and users are limited to increasing the size of the primary instance only.

  3. Global Distribution: MongoDB Atlas provides support for global clusters, allowing users to easily distribute their data across multiple regions for better performance and data redundancy. Amazon DocumentDB, on the other hand, does not currently offer global distribution and is limited to a single region.

  4. Compatibility: MongoDB Atlas is fully compatible with the MongoDB API, which means that applications developed for MongoDB can be easily migrated to MongoDB Atlas without any code changes. Amazon DocumentDB is compatible with a subset of the MongoDB API, which may require some modifications to the existing codebase for migration.

  5. Backup and Recovery: MongoDB Atlas offers a comprehensive backup solution with point-in-time restore capabilities, allowing users to easily recover from data loss or system failures. Amazon DocumentDB also provides backup functionality, but lacks the point-in-time restore feature, making the recovery process more cumbersome and time-consuming.

  6. Supported Features: MongoDB Atlas supports the full range of MongoDB features, including transactions, text search, and geospatial queries. Amazon DocumentDB, although based on the MongoDB framework, does not currently support all MongoDB features. Some advanced functionalities may be limited or not available in Amazon DocumentDB.

In summary, Amazon DocumentDB and MongoDB Atlas differ in their pricing models, scalability options, global distribution capabilities, compatibility with MongoDB API, backup and recovery features, and support for advanced MongoDB functionalities.

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Pros of Amazon DocumentDB
Pros of MongoDB Atlas
  • 0
    Storage elasticity
  • 0
    Scalable
  • 0
    Easy Setup
  • 10
    MongoDB SaaS for and by Mongo, makes it so easy
  • 6
    Amazon VPC peering
  • 4
    Granular role-based access controls
  • 4
    MongoDB atlas is GUItool through you can manage all DB
  • 3
    Use it anywhere
  • 3
    Cloud instance to be worked with
  • 3
    Built-in data browser
  • 1
    Simple and easy to integrate

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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 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.

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What are some alternatives to Amazon DocumentDB and MongoDB Atlas?
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.
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.
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.
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
See all alternatives