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Amazon DynamoDB vs Amazon ElastiCache: What are the differences?
Amazon DynamoDB: Fully managed NoSQL database service. All data items are stored on Solid State Drives (SSDs), and are replicated across 3 Availability Zones for high availability and durability. With DynamoDB, 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; Amazon ElastiCache: Deploy, operate, and scale an in-memory cache in the cloud. 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.
Amazon DynamoDB can be classified as a tool in the "NoSQL Database as a Service" category, while Amazon ElastiCache is grouped under "Managed Memcache".
Some of the features offered by Amazon DynamoDB are:
- 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. If your throughput requirements change, simply update your table's request capacity using the AWS Management Console or the Amazon DynamoDB APIs. You are still able to achieve your prior throughput levels while scaling is underway.
- Fully Distributed, Shared Nothing Architecture – Amazon DynamoDB scales horizontally and can seamlessly scale a single table over hundreds of servers.
On the other hand, Amazon ElastiCache provides the following key features:
- 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.
"Predictable performance and cost" is the top reason why over 53 developers like Amazon DynamoDB, while over 53 developers mention "Redis" as the leading cause for choosing Amazon ElastiCache.
Lyft, New Relic, and Sellsuki are some of the popular companies that use Amazon DynamoDB, whereas Amazon ElastiCache is used by Instacart, SendGrid, and Sellsuki. Amazon DynamoDB has a broader approval, being mentioned in 429 company stacks & 173 developers stacks; compared to Amazon ElastiCache, which is listed in 342 company stacks and 79 developer stacks.
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?
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.
Pros of Amazon DynamoDB
- Predictable performance and cost62
- Scalable56
- Native JSON Support35
- AWS Free Tier21
- Fast7
- No sql3
- To store data3
- Serverless2
- No Stored procedures is GOOD2
- ORM with DynamoDBMapper1
- Elastic Scalability using on-demand mode1
- Elastic Scalability using autoscaling1
- DynamoDB Stream1
Pros of Amazon ElastiCache
- Redis57
- High-performance32
- Backed by amazon26
- Memcached21
- Elastic14
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Cons of Amazon DynamoDB
- Only sequential access for paginate data4
- Scaling1
- Document Limit Size1