Amazon DynamoDB vs Amazon ElastiCache

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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.

Advice on Amazon DynamoDB and Amazon ElastiCache

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?

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Replies (1)
William Frank
Data Science and Engineering at GeistM · | 2 upvotes · 109.7K views

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.

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Pros of Amazon DynamoDB
Pros of Amazon ElastiCache
  • 62
    Predictable performance and cost
  • 56
  • 35
    Native JSON Support
  • 21
    AWS Free Tier
  • 7
  • 3
    No sql
  • 3
    To store data
  • 2
  • 2
    No Stored procedures is GOOD
  • 1
    ORM with DynamoDBMapper
  • 1
    Elastic Scalability using on-demand mode
  • 1
    Elastic Scalability using autoscaling
  • 1
    DynamoDB Stream
  • 58
  • 32
  • 26
    Backed by amazon
  • 21
  • 14

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Cons of Amazon DynamoDB
Cons of Amazon ElastiCache
  • 4
    Only sequential access for paginate data
  • 1
  • 1
    Document Limit Size
    Be the first to leave a con

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    What is Amazon DynamoDB?

    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.

    What is Amazon ElastiCache?

    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.

    Need advice about which tool to choose?Ask the StackShare community!

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    What are some alternatives to Amazon DynamoDB and Amazon ElastiCache?
    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.
    MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
    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.
    The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
    Amazon S3
    Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web
    See all alternatives