Amazon DynamoDB vs Dynomite

Overview

Amazon DynamoDB

Stacks4.0K

Followers3.2K

Votes195

Dynomite

Stacks20

Followers56

Votes9

GitHub Stars4.2K

Forks532

Amazon DynamoDB vs Dynomite: What are the differences?

Data Model: Amazon DynamoDB is a fully managed NoSQL database service that supports key-value and document data structures with the flexibility to add nested attributes. On the other hand, Dynomite is an open-source distributed key-value store that is protocol-compatible with Amazon DynamoDB but follows a simpler data model supporting only key-value pairs without nested attributes.
Consistency Levels: Amazon DynamoDB offers eventual consistency and strong consistency models for reads and writes, allowing users to choose between performance and consistency. In contrast, Dynomite supports eventual consistency by default, with an option to enable strong consistency on a per-operation basis.
Deployment Options: DynamoDB is offered as a fully managed service by Amazon Web Services, allowing users to focus on application development without worrying about infrastructure management. Dynomite, on the other hand, can be deployed on-premises or on cloud platforms like AWS, providing users with more control over their infrastructure but requiring manual setup and maintenance.
Performance Tuning: Amazon DynamoDB automatically handles partitioning, replication, and performance optimization based on user requirements and usage patterns. Dynomite requires manual configuration and tuning for partitioning, sharding, and performance optimization, making it more customizable but also more complex to manage.
Scalability: DynamoDB automatically scales storage and throughput capacity to handle increasing workloads and can effortlessly manage bursty traffic patterns. Dynomite allows manual partitioning and sharding for scalability but may require additional monitoring and adjustment to accommodate growth and changes in workload requirements.
Community Support: Amazon DynamoDB has a large user base and extensive documentation provided by AWS, ensuring robust support and resources for developers. Dynomite, being an open-source project, relies on community contributions and may have limited official support, requiring users to rely on community forums and resources for assistance.

In Summary, Amazon DynamoDB and Dynomite differ in their data models, consistency levels, deployment options, performance tuning, scalability features, and community support.

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Advice on Amazon DynamoDB, Dynomite

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.

1.35k views1.35k

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	Dynomite
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.	Dynomite is a generic dynamo implementation that can be used with many different key-value pair storage engines. Currently these include Redis and Memcached. Dynomite supports multi-datacenter replication and is designed for high availability.
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	Replication;Highly available reads;Pluggable Datastores;Standard open source Memcached/Redis ASCII protocol support;Scalable I/O event notification server;Peer-to-peer, and linearly scalable;Cold cache warm-up;Asymmetric multi-datacenter replications;Internode communication and Gossip;Functional in AWS and physical datacenter
Statistics
GitHub Stars -	GitHub Stars 4.2K
GitHub Forks -	GitHub Forks 532
Stacks 4.0K	Stacks 20
Followers 3.2K	Followers 56
Votes 195	Votes 9
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 3 Multi datacenters or regions 2 Pluggable APIs (Currently have Redis/Memcached APIs) 2 Low latency high throughput 1 Support many datastores: redis, memcached, rocksdb, etc 1 Scale
Integrations
Amazon RDS for PostgreSQL PostgreSQL MySQL SQLite Azure Database for MySQL	Redis Memcached

What are some alternatives to Amazon DynamoDB, Dynomite?

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.

Navicat

Powerful database management & design tool for Win, Mac & Linux. With intuitive GUI, user manages MySQL, MariaDB, SQL Server, SQLite, Oracle & PostgreSQL DB easily.

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 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 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.

Related Comparisons

Amazon DynamoDB vs Dynomite: What are the differences?

Data Model: Amazon DynamoDB is a fully managed NoSQL database service that supports key-value and document data structures with the flexibility to add nested attributes. On the other hand, Dynomite is an open-source distributed key-value store that is protocol-compatible with Amazon DynamoDB but follows a simpler data model supporting only key-value pairs without nested attributes.
Consistency Levels: Amazon DynamoDB offers eventual consistency and strong consistency models for reads and writes, allowing users to choose between performance and consistency. In contrast, Dynomite supports eventual consistency by default, with an option to enable strong consistency on a per-operation basis.
Deployment Options: DynamoDB is offered as a fully managed service by Amazon Web Services, allowing users to focus on application development without worrying about infrastructure management. Dynomite, on the other hand, can be deployed on-premises or on cloud platforms like AWS, providing users with more control over their infrastructure but requiring manual setup and maintenance.
Performance Tuning: Amazon DynamoDB automatically handles partitioning, replication, and performance optimization based on user requirements and usage patterns. Dynomite requires manual configuration and tuning for partitioning, sharding, and performance optimization, making it more customizable but also more complex to manage.
Scalability: DynamoDB automatically scales storage and throughput capacity to handle increasing workloads and can effortlessly manage bursty traffic patterns. Dynomite allows manual partitioning and sharding for scalability but may require additional monitoring and adjustment to accommodate growth and changes in workload requirements.
Community Support: Amazon DynamoDB has a large user base and extensive documentation provided by AWS, ensuring robust support and resources for developers. Dynomite, being an open-source project, relies on community contributions and may have limited official support, requiring users to rely on community forums and resources for assistance.

In Summary, Amazon DynamoDB and Dynomite differ in their data models, consistency levels, deployment options, performance tuning, scalability features, and community support.

Amazon DynamoDB vs Dynomite

Overview