Amazon DynamoDB vs restdb.io

Overview

Amazon DynamoDB

Stacks4.0K

Followers3.2K

Votes195

restdb.io

Stacks13

Followers27

Votes2

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.

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.
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.
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.
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.
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.
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.

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Advice on Amazon DynamoDB, restdb.io

Doru

Solution Architect

Jun 9, 2019

Reviewon

Amazon DynamoDB

I use Amazon DynamoDB because it integrates seamlessly with other AWS SaaS solutions and if cost is the primary concern early on, then this will be a better choice when compared to AWS RDS or any other solution that requires the creation of a HA cluster of IaaS components that will cost money just for being there, the costs not being influenced primarily by usage.

1.34k views1.34k

Comments

akash

Aug 27, 2020

Needs adviceon

Cloud Firestore

Firebase Realtime Database

Amazon DynamoDB

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?

199k views199k

Comments

Detailed Comparison

Amazon DynamoDB	restdb.io
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.	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.
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	NoSQL + Schema + API; Rich Data Types, Relations and Hierarchy; Data Management and Collaboration web app; Media Archive; Random Data Generator; HTML Pages inside database; Excel,CSV,JSON Import and Export of data; Webhooks, Auth0 external user Authentication
Statistics
Stacks 4.0K	Stacks 13
Followers 3.2K	Followers 27
Votes 195	Votes 2
Pros & Cons
Pros 62 Predictable performance and cost 56 Scalable 35 Native JSON Support 21 AWS Free Tier 7 Fast Cons 4 Only sequential access for paginate data 1 Scaling 1 Document Limit Size	Pros 2 Easy, yet powerful, db setup and management
Integrations
Amazon RDS for PostgreSQL PostgreSQL MySQL SQLite Azure Database for MySQL	Zapier Auth0

What are some alternatives to Amazon DynamoDB, restdb.io?

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.

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.

Cloudant

Cloudant’s distributed database as a service (DBaaS) allows developers of fast-growing web and mobile apps to focus on building and improving their products, instead of worrying about scaling and managing databases on their own.

Google Cloud Bigtable

Google Cloud Bigtable offers you a fast, fully managed, massively scalable NoSQL database service that's ideal for web, mobile, and Internet of Things applications requiring terabytes to petabytes of data. Unlike comparable market offerings, Cloud Bigtable doesn't require you to sacrifice speed, scale, or cost efficiency when your applications grow. Cloud Bigtable has been battle-tested at Google for more than 10 years—it's the database driving major applications such as Google Analytics and Gmail.

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.

CloudBoost

CloudBoost.io is a database service for the “next web” - that not only does data-storage, but also search, real-time and a whole lot more which enables developers to build much richer apps with 50% less time saving them a ton of cost and helping them go to market much faster.

Firebase Realtime Database

It is a cloud-hosted NoSQL database that lets you store and sync data between your users in realtime. Data is synced across all clients in realtime, and remains available when your app goes offline.

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.

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.

Aiven

A fully-managed and hosted database as a service (DBaaS) that provides enterprises of every size access to secure and scalable open-source database and messaging services on all major clouds across the globe.

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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.

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.
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.
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.
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.
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.
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.