Amazon DynamoDB vs Azure Cosmos DB vs Cloud Firestore

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Amazon DynamoDB

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Azure Cosmos DB

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Cloud Firestore

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Amazon DynamoDB vs Azure Cosmos DB vs Cloud Firestore: What are the differences?

Introduction

This Markdown code provides a comparison between Amazon DynamoDB, Azure Cosmos DB, and Cloud Firestore to highlight their key differences.

  1. Scalability: Amazon DynamoDB and Azure Cosmos DB are both known for their high scalability, allowing users to easily scale up or down their database resources based on demand. Cloud Firestore, on the other hand, offers automatic scaling without the need for manual intervention, making it a more hands-off option for users.

  2. Consistency Models: Azure Cosmos DB offers five different consistency levels, allowing users to choose between strong consistency, Bounded staleness, Session consistency, Strong consistency, and Eventual consistency based on their application's requirements. Amazon DynamoDB and Cloud Firestore, however, have limited options in terms of consistency models, with DynamoDB offering eventual consistency or strong consistency and Cloud Firestore providing strong consistency by default with eventual consistency available as well.

  3. Pricing: Amazon DynamoDB and Azure Cosmos DB have different pricing models based on provisioned throughput and usage, which can make cost estimation challenging. Cloud Firestore, on the other hand, offers a simpler pricing structure based on the number of reads, writes, and deletes, making it easier for users to predict costs.

  4. Data Model: Amazon DynamoDB and Azure Cosmos DB support flexible data models, allowing users to store various types of data including JSON, BLOBs, and tabular data. Cloud Firestore is more focused on document-based data modeling, making it ideal for applications that require structured data storage.

  5. Query Language: Azure Cosmos DB supports SQL-like queries with its SQL API, making it easy for developers familiar with SQL to query data. Amazon DynamoDB and Cloud Firestore, however, have limited querying capabilities, with DynamoDB requiring the use of secondary indexes and Cloud Firestore offering basic query functionalities.

  6. Global Distribution: Azure Cosmos DB offers global distribution out of the box, allowing users to replicate data across multiple regions for low-latency access worldwide. Amazon DynamoDB and Cloud Firestore also support global distribution but may require additional configuration and setup to achieve similar levels of global availability.

In Summary, the key differences between Amazon DynamoDB, Azure Cosmos DB, and Cloud Firestore lie in scalability, consistency models, pricing, data models, query languages, and global distribution capabilities.

Advice on Amazon DynamoDB, Azure Cosmos DB, and Cloud Firestore

We are building a social media app, where users will post images, like their post, and make friends based on their interest. We are currently using Cloud Firestore and Firebase Realtime Database. We are looking for another database like Amazon DynamoDB; how much this decision can be efficient in terms of pricing and overhead?

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Replies (1)
William Frank
Data Science and Engineering at GeistM · | 2 upvotes · 107.3K views
Recommends

Hi, Akash,

I wouldn't make this decision without lots more information. Cloud Firestore has a much richer metamodel (document-oriented) than Dynamo (key-value), and Dynamo seems to be particularly restrictive. That is why it is so fast. There are many needs in most applications to get lightning access to the members of a set, one set at a time. Dynamo DB is a great choice. But, social media applications generally need to be able to make long traverses across a graph. While you can make almost any metamodel act like another one, with your own custom layers on top of it, or just by writing a lot more code, it's a long way around to do that with simple key-value sets. It's hard enough to traverse across networks of collections in a document-oriented database. So, if you are moving, I think a graph-oriented database like Amazon Neptune, or, if you might want built-in reasoning, Allegro or Ontotext, would take the least programming, which is where the most cost and bugs can be avoided. Also, managed systems are also less costly in terms of people's time and system errors. It's easier to measure the costs of managed systems, so they are often seen as more costly.

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Pros of Amazon DynamoDB
Pros of Azure Cosmos DB
Pros of Cloud Firestore
  • 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
  • 28
    Best-of-breed NoSQL features
  • 22
    High scalability
  • 15
    Globally distributed
  • 14
    Automatic indexing over flexible json data model
  • 10
    Tunable consistency
  • 10
    Always on with 99.99% availability sla
  • 7
    Javascript language integrated transactions and queries
  • 6
    Predictable performance
  • 5
    High performance
  • 5
    Analytics Store
  • 2
    Rapid Development
  • 2
    No Sql
  • 2
    Auto Indexing
  • 2
    Ease of use
  • 15
    Easy to use
  • 15
    Cloud Storage
  • 12
    Realtime Database
  • 12
    Easy setup
  • 9
    Super fast
  • 8
    Authentication
  • 6
    Realtime listeners
  • 5
    Could Messaging
  • 5
    Hosting
  • 5
    Google Analytics integration
  • 4
    Performance Monitoring
  • 4
    Crash Reporting
  • 3
    Sharing App via invites
  • 3
    Test Lab for Android
  • 3
    Adwords, Admob integration
  • 2
    Dynamic Links (Deeplinking support)
  • 0
    Robust ALI

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Cons of Amazon DynamoDB
Cons of Azure Cosmos DB
Cons of Cloud Firestore
  • 4
    Only sequential access for paginate data
  • 1
    Scaling
  • 1
    Document Limit Size
  • 18
    Pricing
  • 4
    Poor No SQL query support
  • 8
    Doesn't support FullTextSearch natively

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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.

What is Azure Cosmos DB?

Azure DocumentDB is a fully managed NoSQL database service built for fast and predictable performance, high availability, elastic scaling, global distribution, and ease of development.

What is 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.

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What companies use Amazon DynamoDB?
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What companies use Cloud Firestore?

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What tools integrate with Amazon DynamoDB?
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What are some alternatives to Amazon DynamoDB, Azure Cosmos DB, and Cloud Firestore?
Google Cloud Datastore
Use a managed, NoSQL, schemaless database for storing non-relational data. Cloud Datastore automatically scales as you need it and supports transactions as well as robust, SQL-like queries.
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.
Amazon SimpleDB
Developers simply store and query data items via web services requests and Amazon SimpleDB does the rest. Behind the scenes, Amazon SimpleDB creates and manages multiple geographically distributed replicas of your data automatically to enable high availability and data durability. Amazon SimpleDB provides a simple web services interface to create and store multiple data sets, query your data easily, and return the results. Your data is automatically indexed, making it easy to quickly find the information that you need. There is no need to pre-define a schema or change a schema if new data is added later. And scale-out is as simple as creating new domains, rather than building out new servers.
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.
Amazon S3
Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web
See all alternatives