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DynamoDB vs Memcached - The Ultimate Comparison

Poorna Theekshana

Written by Poorna Theekshana

Published on November 20th, 2022

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    Amazon DynamoDB and Memcached are two popular NoSQL database solutions that support key-value pair data storage formats. This article will discuss the similarities and differences between these two to help you decide when to use which database service.

    DynamoDB vs. Memcached: An Overview

    Amazon DynamoDB is a fully managed NoSQL database service provided by Amazon. It ensures millisecond latency at any scale and supports key-value and document data. DynamoDB provides excellent features like security, backups, caching (using DAX), and scalability to help developers create reliable applications.

    Memcached is an open-source, high-performance distributed memory object caching system. It can be utilized as a cache or session store since it provides an established, scalable solution for delivering sub-millisecond response speeds. Therefore, Memcached is a great option for real-time data processing, mobile apps, games, and e-commerce applications.

    Shared Features of DynamoDB and Memcached

    DynamoDB and Memcached are high-performance, robust, and reliable NoSQL databases. They use the key-value store as the primary database model, while DynamoDB also supports the document model.

    Furthermore, both DynamoDB and Memcached can be used for caching purposes. However, Memcached is more specialized as a general-purpose distributed memory-caching system.

    Latency and Performance

    DynamoDB

    DynamoDB is a powerful NoSQL database solution that maintains single-digit millisecond latency at any scale. It can manage 10 trillion daily requests and up to 20 million requests per second without affecting performance.

    DynamoDB SSDs will ensure minimum latency and response times when reading and writing records, regardless of your table size. You can further improve these rates by using indexes and keys to streamline the database workload. In addition, you can use the in-memory cache for DynamoDB (DynamoDB Accelerator) to reduce the latency and response times (from milliseconds to microseconds) by ten times at any scale.

    Memcached

    Similar to DynamoDB, Memcached is also designed for high performance. With the correct underline hardware, Memcached can handle up to 200,000+ requests per second while maintaining a response time of less than a millisecond.

    Availability and Durability

    DynamoDB

    To ensure high availability, DynamoDB replicates data across multiple availability zones. For instance, AWS will automatically copy your table across three availability zones in a chosen region. It ensures high data availability and durability even in natural disasters like fires, earthquakes, and power outages.

    Additionally, you can use DynamoDB global tables to replicate your DynamoDB tables across multiple regions to enhance high availability and durability.

    Memcached

    Unlike DynamoDB, Memcached does not provide any built-in features to maintain high availability. However, this is not a significant issue since Memcached is mostly sued as a cache to reduce the load on the database.

    Security

    DynamoDB

    DynamoDB supports encryption at rest using the encryption keys kept in AWS KMS (AWS Key Management Service). Users can choose between using a user-managed key, an AWS-owned key, or an AWS-managed key for encryption.

    In addition, IAM (Identity and Access Management) roles can be used to authenticate access to DynamoDB tables. By defining IAM policies, you can restrict access to specific users, user groups, or roles.

    Memcached

    Compared to DynamoDB, Memcached have fewer security measurements since it is mostly deployed in secure networks. However, there can be situations where we can't ensure network security. Hence, the latest versions of Memcached are configured to run with SASL authentication. In addition, you can manually configure TLS encryption to Memcached if your client is compatible with TLS encryption.

    Scalability

    DynamoDB

    DynamoDB is a highly scalable service. It can support any table size and seamlessly scales according to the workload. High scalability has zero effect on application performance, and you can choose one of its two capacity modes to decide the scaling behavior.

    • On-Demand Capacity Mode: DynamoDB tables are automatically scaled up and down depending on the workload. It is suited for ad-hoc traffic.
    • Provisioned Capacity Mode: In the provisioned capacity mode, the user must specify the auto-scaling configurations, including the minimum and maximum number of capacity units. Appropriate for regular traffic.

    Memcached

    High scalability is a highlighted feature of Memcached. The Memcached engine allows you to divide your data among several nodes. A Memcached cluster can contain up to forty nodes and can add or remove nodes horizontally based on the workload.

    Backups & Restore

    DynamoDB

    DynamoDb provides two main backup options: Point-in-time backups (PITR) and on-demand backups.

    • On-demand backups: Creates full backup of the DynamoDB table. Suitable for long-time data retention purposes and need to configure the backups manually.
    • Point-in-time recovery (PITR): Once enabled, PITR automatically creates continuous backups of your DynamoDB tables. It will keep the records for 35 days allowing you to restore the data to any second within the preceding 35 days.

    Memcached

    Memcached provides several libraries to help developers in creating backups.

    • Memcached Utility - Allows to backup and restore data in Memcached cache when stopping and restarting the Memcached server.
    • memdump - Allows dumping a list of "keys" from all Memcached servers. However, it does not ensure getting all the keys since Memcached does not provide complete dumps.
    • memcat - Allows copying single or multiple keys stored in Memcached servers.

    Pricing

    DynamoDB

    The cost of DynamoDB core features is determined by the usage. However, the cost can be changed from user to user based on the additional services they use. DynamoDb provides two pricing models to choose from:

    • On-demand capacity mode: The total cost for read and write units will be decided based on the traffic volume. Good for unpredictable traffics.
    • Provisioned Capacity Mode: The entire cost will depend on the user-specified read and write capacity units in the provisioned capacity mode. Good for predictable traffics.

    Additionally, the DynamoDB free tier offers 100 GB of data transfers, 25 GB of data storage, and 2.5 million streams of read requests.

    Memcached

    Memcached caching is a distributed memory object system that is free and open source (BSD license). Therefore, there are no fees associated with using Memcached.

    When to Use Which

    Use cases for DynamoDB

    DynamoDB can be an excellent option when a No-SQL database system is required, and the user already uses AWS. Additionally, DynamoDB can be used for tasks that need automatic scaling, high availability, and consistent performance.

    Here are some of the common application types where you can use DynamoDB:

    • Real-time data processing application
    • E commerce applications
    • Mobile application
    • Games
    • Applications with high IO needs
    • Content management

    Use cases for Memcached

    Memcached is an excellent option for setting up high-performance in-memory caches and session stores. It reduces the stress on your database while boosting the throughput and reducing the data access latency. Hence, Memcached is widely used for caching database query results, sessions, web pages, APIs, and objects like images, files, and metadata.

    Here are some of the common application types where you can use Memcached:

    • Shopping carts
    • Games
    • Mobile applications

    Conclusion

    In this article, I have discussed DynamoDB and Memcached memory caching systems. Understanding their advantages, disadvantages, differences, and limitations will help you to decide which service is best for your use case.

    I hope that you found this article helpful! Thank you for reading!

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