Amazon DynamoDB vs restdb.io

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

Amazon DynamoDB

3.7K
3.2K
+ 1
195
restdb.io

13
27
+ 1
2
Add tool

Amazon DynamoDB vs restdb.io: What are the differences?

Introduction

When comparing Amazon DynamoDB and restdb.io, it is important to note the key differences between the two database management systems.

  1. Data Model: Amazon DynamoDB follows a NoSQL database model, specializing in key-value and document data, while restdb.io is based on a RESTful API model, offering a more flexible schema for data storage and retrieval.

  2. Scalability: DynamoDB is fully managed by Amazon Web Services (AWS), allowing for seamless scaling of throughput and storage based on demand, while restdb.io offers scalable infrastructure but requires manual configuration for scaling needs.

  3. Pricing: DynamoDB operates on a pay-per-usage pricing model, where users are charged based on the provisioned throughput capacity and storage used, while restdb.io has a subscription-based pricing model, which includes various tiers based on usage and features.

  4. ACID Compliance: Amazon DynamoDB ensures ACID (Atomicity, Consistency, Isolation, Durability) compliance for data transactions, offering strong data consistency and durability, while restdb.io may not guarantee the same level of ACID compliance, depending on the nature of the RESTful API interactions.

  5. Data Querying: DynamoDB offers powerful querying capabilities with secondary indexes and query optimization tools, allowing for efficient data retrieval, whereas restdb.io relies on RESTful API endpoints for data retrieval, which may not provide the same level of flexibility and optimization for complex queries.

  6. Monitoring and Management: AWS provides comprehensive monitoring and management tools for DynamoDB, including metrics, alarms, and auto-scaling features, while restdb.io offers basic monitoring capabilities but may lack advanced management tools compared to a cloud-based service like DynamoDB.

In Summary, Amazon DynamoDB and restdb.io differ in their data models, scalability options, pricing structures, ACID compliance, data querying capabilities, and monitoring and management tools.

Advice on Amazon DynamoDB and restdb.io

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?

See more
Replies (1)
William Frank
Data Science and Engineering at GeistM · | 2 upvotes · 107.9K 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.

See more
Get Advice from developers at your company using StackShare Enterprise. Sign up for StackShare Enterprise.
Learn More
Pros of Amazon DynamoDB
Pros of restdb.io
  • 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
  • 2
    Easy, yet powerful, db setup and management

Sign up to add or upvote prosMake informed product decisions

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

    Sign up to add or upvote consMake informed product decisions

    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 restdb.io?

    RestDB is a NoSql document oriented database cloud service. Data is accessed as JSON objects via HTTPS. This gives great flexibility, easy system integration and future compatibility.

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

    What companies use Amazon DynamoDB?
    What companies use restdb.io?
    See which teams inside your own company are using Amazon DynamoDB or restdb.io.
    Sign up for StackShare EnterpriseLearn More

    Sign up to get full access to all the companiesMake informed product decisions

    What tools integrate with Amazon DynamoDB?
    What tools integrate with restdb.io?

    Sign up to get full access to all the tool integrationsMake informed product decisions

    Blog Posts

    GitHubPythonNode.js+47
    54
    72317
    GitHubGitSlack+30
    27
    18325
    GitHubDockerAmazon EC2+23
    12
    6566
    GitHubPythonSlack+25
    7
    3155
    DockerSlackAmazon EC2+17
    18
    5969
    What are some alternatives to Amazon DynamoDB and restdb.io?
    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