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  1. Stackups
  2. Application & Data
  3. NoSQL Databases
  4. NOSQL Database As A Service
  5. Amazon DynamoDB vs Datomic Cloud

Amazon DynamoDB vs Datomic Cloud

OverviewDecisionsComparisonAlternatives

Overview

Amazon DynamoDB
Amazon DynamoDB
Stacks4.0K
Followers3.2K
Votes195
Datomic Cloud
Datomic Cloud
Stacks15
Followers25
Votes0

Amazon DynamoDB vs Datomic Cloud: What are the differences?

Introduction

When considering database services for your application, it's important to understand the key differences between Amazon DynamoDB and Datomic Cloud. Both services offer scalable, reliable, and highly available solutions for different use cases. Here are the key differences between the two services:

  1. Data Model: Amazon DynamoDB is a NoSQL database that uses a key-value and document data model, allowing for flexibility in storing different types of data. On the other hand, Datomic Cloud is a database that uses an entity-attribute-value model, providing a more structured approach to data storage.

  2. Consistency Model: Amazon DynamoDB offers eventual consistency by default, with the option to choose strong consistency if required. In contrast, Datomic Cloud provides strong consistency out of the box, ensuring that all reads reflect the latest writes to the system.

  3. Query Language: Amazon DynamoDB uses a proprietary query language and API for data retrieval and manipulation. Datomic Cloud, on the other hand, utilizes Datalog, a declarative query language that allows for expressive and powerful queries over the database.

  4. Data Storage: Amazon DynamoDB is primarily designed for operational data storage, offering fast and predictable performance for read and write operations. Datomic Cloud, on the other hand, is optimized for transactional data storage, providing a full audit history of changes made to the data over time.

  5. Scaling: Amazon DynamoDB allows for scaling by increasing read and write capacity units to meet the application's demands. Datomic Cloud, on the other hand, offers horizontal scaling by adding additional storage nodes to handle increased workload and storage requirements.

  6. Data Security: Amazon DynamoDB provides encryption at rest and in transit to secure data stored in the database. Datomic Cloud offers fine-grained access control and audit logging to restrict access to sensitive data and track changes made to the database.

In Summary, understanding the key differences between Amazon DynamoDB and Datomic Cloud can help in choosing the right database service for your specific application requirements.

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Advice on Amazon DynamoDB, Datomic Cloud

Doru
Doru

Solution Architect

Jun 9, 2019

ReviewonAmazon DynamoDBAmazon 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
akash

Aug 27, 2020

Needs adviceonCloud FirestoreCloud FirestoreFirebase Realtime DatabaseFirebase Realtime DatabaseAmazon DynamoDBAmazon 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
Amazon DynamoDB
Datomic Cloud
Datomic Cloud

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.

A transactional database with a flexible data model, elastic scaling, and rich queries. Datomic is designed from the ground up to run on AWS. Datomic leverages AWS technology, including DynamoDB, S3, EFS, and CloudFormation to provide a fully integrated solution.

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
Scaling; Reliability and Availability; Security; Storage; Pay-per-usage (no contracts); Monitoring; Fully automated deployment and operational control via AWS CloudFormation; Agility
Statistics
Stacks
4.0K
Stacks
15
Followers
3.2K
Followers
25
Votes
195
Votes
0
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
No community feedback yet
Integrations
Amazon RDS for PostgreSQL
Amazon RDS for PostgreSQL
PostgreSQL
PostgreSQL
MySQL
MySQL
SQLite
SQLite
Azure Database for MySQL
Azure Database for MySQL
AWS CloudFormation
AWS CloudFormation
Amazon VPC
Amazon VPC
AWS IAM
AWS IAM
Amazon S3
Amazon S3
Amazon EFS
Amazon EFS
Amazon CloudWatch
Amazon CloudWatch

What are some alternatives to Amazon DynamoDB, Datomic Cloud?

Azure Cosmos DB

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

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

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

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

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

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

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.

restdb.io

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.

Amazon DocumentDB

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

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.

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