Amazon DynamoDB vs Cloud Firestore

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Amazon DynamoDB

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Amazon DynamoDB vs Cloud Firestore: What are the differences?

Differences between Amazon DynamoDB and Cloud Firestore

Amazon DynamoDB and Cloud Firestore are two popular NoSQL databases that are widely used for building modern, scalable web applications. While they share some similarities, there are several key differences between these two platforms. The following paragraphs highlight six important distinctions that set them apart.

  1. Data Model: Amazon DynamoDB is a key-value store that provides fast and predictable performance with the ability to scale horizontally. It is schema-less and allows flexible data modeling. On the other hand, Cloud Firestore is a document-based database that organizes data into documents and collections. It supports more complex data structures with nested fields and arrays, making it easier to represent hierarchical data.

  2. Scalability: Both DynamoDB and Cloud Firestore are designed to handle scale, but they have different scaling approaches. In DynamoDB, scaling is done based on read and write capacity units, providing fine-grained control over resource allocation. Cloud Firestore, on the other hand, automatically scales to handle read and write traffic, making it easier to handle sudden spikes in workloads without manual capacity planning.

  3. Pricing Model: DynamoDB uses a provisioned capacity model, where users need to provision and pay for the read and write capacity units they require. This provides cost predictability but can lead to over or under-provisioning. Cloud Firestore, on the other hand, uses a pay-as-you-go model, where users are billed based on the number of document reads, writes, and storage used. This gives more flexibility in terms of cost management.

  4. Real-time Updates: Cloud Firestore has built-in real-time data synchronization, allowing clients to receive updates in real-time. It uses web sockets and provides real-time listeners that notify clients whenever a document changes. DynamoDB, on the other hand, does not have built-in real-time capabilities and requires the use of additional services like AWS Lambda or Amazon Kinesis to achieve similar functionality.

  5. Query Capabilities: DynamoDB provides powerful and flexible querying options through its Query and Scan operations. It allows filtering based on various attributes and supports secondary indexes for better query performance. Cloud Firestore also offers querying capabilities, but its querying model is more limited compared to DynamoDB. Queries rely on simple equality and range comparisons and do not support complex filtering or secondary indexes.

  6. Integration with Ecosystem: DynamoDB is part of the Amazon Web Services (AWS) ecosystem, which provides a broad range of complementary services like AWS Lambda, AWS CloudFormation, and Amazon S3. This tight integration allows developers to build end-to-end solutions using multiple AWS services. Cloud Firestore, on the other hand, is part of the Google Cloud ecosystem and integrates well with other Google Cloud Platform services like Cloud Functions, Firebase Authentication, and Cloud Storage.

In summary, Amazon DynamoDB and Cloud Firestore differ in their data models, scalability approaches, pricing models, real-time capabilities, query capabilities, and integration with their respective ecosystems. Each platform has its strengths and weaknesses, and the choice between them depends on the specific requirements of the project and the preferences of the development team.

Advice on Amazon DynamoDB 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 · 108.8K 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 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
  • 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 Cloud Firestore
  • 4
    Only sequential access for paginate data
  • 1
    Scaling
  • 1
    Document Limit Size
  • 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 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?
What companies use Cloud Firestore?
See which teams inside your own company are using Amazon DynamoDB or Cloud Firestore.
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What are some alternatives to Amazon DynamoDB 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