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

Amazon DynamoDB vs Amazon ElastiCache

OverviewDecisionsComparisonAlternatives

Overview

Amazon DynamoDB
Amazon DynamoDB
Stacks4.0K
Followers3.2K
Votes195
Amazon ElastiCache
Amazon ElastiCache
Stacks1.3K
Followers1.0K
Votes151

Amazon DynamoDB vs Amazon ElastiCache: What are the differences?

Amazon DynamoDB and Amazon ElastiCache are two managed services offered by Amazon Web Services (AWS). Let's explore the key differences between them.

  1. Scalability and Performance: Amazon DynamoDB is a NoSQL database service that offers automatic scaling and provides consistent single-digit millisecond latency even at scale. It can handle millions of requests per second and can effortlessly scale horizontally to support growing workloads. On the other hand, Amazon ElastiCache is an in-memory caching service that enhances the performance of web applications by retrieving frequently accessed data from a fast, in-memory cache rather than relying on slower disk-based databases. It improves application responsiveness and supports high throughput and low-latency read and write operations.

  2. Data Persistence: DynamoDB is designed to provide durability and availability by automatically replicating data across multiple Availability Zones within a region. It is a fully-managed service where data is automatically replicated and backed up. In contrast, ElastiCache is an in-memory data store that is non-persistent by nature. It relies on databases like DynamoDB, Amazon RDS, or even files systems for persistent storage.

  3. Data Structures and Querying: DynamoDB is a key-value store that allows applications to store and retrieve any amount of data using primary key attributes. It provides fast and predictable performance with simple read and write operations. Additionally, DynamoDB supports rich querying capabilities through secondary indexes. On the other hand, ElastiCache supports in-memory caching with popular data structures such as strings, hashes, lists, sets, and sorted sets. It offers powerful caching mechanisms, but does not provide the querying capability like DynamoDB.

  4. Primary Use Case: DynamoDB is suitable for applications that require scalable and predictable performance, where the data size can vary and grow rapidly over time. It is commonly used for applications like gaming, mobile, e-commerce, advertising, and IoT platforms. ElastiCache, on the other hand, is intended to boost the performance of existing databases and applications by storing frequently accessed data in-memory. It is commonly used for reducing the load on databases, accelerating read-heavy workloads, and improving application response time.

  5. Data Consistency: DynamoDB offers two types of data consistency models: eventually consistent reads and strongly consistent reads. Entering an eventual consistency model provides lower latency and higher throughput, while strongly consistent reads ensure the most up-to-date data at the cost of higher latency. In contrast, ElastiCache offers eventual consistency only, meaning that data retrieved from the cache may not be the most recent version.

  6. Managed vs Self-Managed Service: DynamoDB is a fully-managed service, meaning that AWS handles the administrative and maintenance tasks associated with database management, such as hardware provisioning, patching, backup, and scaling. On the other hand, ElastiCache is a self-managed service where users are responsible for the deployment, configuration, and maintenance of the caching environment.

In summary, Amazon DynamoDB is a fully-managed NoSQL database service that provides automatic scaling, strong consistency, and rich querying capabilities, making it suitable for scalable and high-performance applications. Amazon ElastiCache, on the other hand, is an in-memory caching service that enhances application performance by storing frequently accessed data in-memory, speeding up read-heavy workloads and reducing the load on databases.

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Advice on Amazon DynamoDB, Amazon ElastiCache

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
Amazon ElastiCache
Amazon ElastiCache

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.

ElastiCache improves the performance of web applications by allowing you to retrieve information from fast, managed, in-memory caches, instead of relying entirely on slower disk-based databases. ElastiCache supports Memcached and Redis.

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
Support for two engines: Memcached and Redis;Ease of management via the AWS Management Console. With a few clicks you can configure and launch instances for the engine you wish to use.;Compatibility with the specific engine protocol. This means most of the client libraries will work with the respective engines they were built for - no additional changes or tweaking required.;Detailed monitoring statistics for the engine nodes at no extra cost via Amazon CloudWatch;Pay only for the resources you consume based on node hours used
Statistics
Stacks
4.0K
Stacks
1.3K
Followers
3.2K
Followers
1.0K
Votes
195
Votes
151
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
  • 58
    Redis
  • 32
    High-performance
  • 26
    Backed by amazon
  • 21
    Memcached
  • 14
    Elastic
Integrations
Amazon RDS for PostgreSQL
Amazon RDS for PostgreSQL
PostgreSQL
PostgreSQL
MySQL
MySQL
SQLite
SQLite
Azure Database for MySQL
Azure Database for MySQL
No integrations available

What are some alternatives to Amazon DynamoDB, Amazon ElastiCache?

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.

MemCachier

MemCachier

MemCachier provides an easy and powerful managed caching solution for all your performance and scalability needs. It works with the ubiquitous memcache protocol so your favourite language and framework already supports it.

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.

Memcached Cloud

Memcached Cloud

Memcached Cloud is a fully-managed service for running your Memcached in a reliable and fail-safe manner. Your dataset is constantly replicated, so if a node fails, an auto-switchover mechanism guarantees data is served without interruption. Memcached Cloud provides various data persistence options as well as remote backups for disaster recovery purposes.

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.

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