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memcached VS GraphQL Cache

Compare memcached VS GraphQL Cache and see what are their differences

memcached logo memcached

High-performance, distributed memory object caching system

GraphQL Cache logo GraphQL Cache

GraphQL provides a complete description of the data in your API, gives clients the power to ask for exactly what they need and nothing more, makes it easier to evolve APIs over time, and enables powerful developer tools.
  • memcached Landing page
    Landing page //
    2023-07-23
  • GraphQL Cache Landing page
    Landing page //
    2023-08-29

memcached features and specs

  • High Performance
    Memcached is incredibly fast and efficient at caching data in memory, enabling quick data retrieval and reducing the load on databases. Its in-memory nature significantly reduces latency.
  • Scalability
    Memcached can be easily scaled horizontally by adding more nodes to the caching cluster. This allows it to handle increased loads and large datasets without performance degradation.
  • Simplicity
    Memcached has a simple design and API, making it easy to implement and use. Developers can quickly integrate it into their applications without a steep learning curve.
  • Open Source
    Memcached is free and open-source software, which means it can be used and modified without any licensing fees. This makes it a cost-effective solution for caching.
  • Language Agnostic
    Memcached supports multiple programming languages through various client libraries, making it versatile and suitable for use in diverse tech stacks.

Possible disadvantages of memcached

  • Data Volatility
    Memcached stores data in RAM, so all cached data is lost if the server is restarted or crashes. This makes it unsuitable for storing critical or persistent data.
  • Limited Data Types
    Memcached primarily supports simple key-value pairs. It lacks the rich data types and more complex structures supported by some other caching solutions like Redis.
  • No Persistence
    Memcached does not offer any data persistence features. It cannot save data to disk, so all information is ephemeral and will be lost on system reset.
  • Size Limitation
    Memcached has a memory limit for each instance, thus, large-scale applications may need to manage multiple instances and ensure data is properly distributed.
  • Security
    Memcached does not provide built-in security features such as authentication or encryption. This can be a concern in environments where data privacy and security are critical.

GraphQL Cache features and specs

No features have been listed yet.

memcached videos

Course Preview: Using Memcached and Varnish to Speed Up Your Linux Web App

GraphQL Cache videos

No GraphQL Cache videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to memcached and GraphQL Cache)
Databases
94 94%
6% 6
NoSQL Databases
94 94%
6% 6
Key-Value Database
93 93%
7% 7
Graph Databases
100 100%
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare memcached and GraphQL Cache

memcached Reviews

Redis vs. KeyDB vs. Dragonfly vs. Skytable | Hacker News
Quick ask: I don’t see “some” of the other offering out there like MemCached… what was the criteria used to select these? I don’t see any source of how the test where run, specs of the systems, how the DB where set up, etc. Would be very valuable to have in order to attempt to re-validate these test on our own platform. I also came back and saw some of your updates...
Memcached vs Redis - More Different Than You Would Expect
So knowing how the difference between Redis and memcached in-memory usage, lets see what this means. Memcached slabs once assigned never change their size. This means it is possible to poison your memcached cluster and really waste memory. If you load your empty memcached cluster with lots of 1 MB items, then all of the slabs will be allocated to that size. Adding a 80 KB...
Redis vs. Memcached: In-Memory Data Storage Systems
Memcached itself does not support distributed mode. You can only achieve the distributed storage of Memcached on the client side through distributed algorithms such as Consistent Hash. The figure below demonstrates the distributed storage implementation schema of Memcached. Before the client side sends data to the Memcached cluster, it first calculates the target node of the...
Source: medium.com
Why Redis beats Memcached for caching
Both Memcached and Redis are mature and hugely popular open source projects. Memcached was originally developed by Brad Fitzpatrick in 2003 for the LiveJournal website. Since then, Memcached has been rewritten in C (the original implementation was in Perl) and put in the public domain, where it has become a cornerstone of modern Web applications. Current development of...

GraphQL Cache Reviews

We have no reviews of GraphQL Cache yet.
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Social recommendations and mentions

Based on our record, memcached should be more popular than GraphQL Cache. It has been mentiond 36 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

memcached mentions (36)

  • MySQL Performance Tuning Techniques
    Memcached can help when lightning-fast performance is needed. These tools store frequently accessed data, such as session details, API responses, or product prices, in RAM. This reduces the laid on your primary database, so you can deliver microsecond response times. - Source: dev.to / 2 months ago
  • 10 Best Practices for API Rate Limiting in 2025
    In-memory tools like Redis or Memcached for fast Data retrieval. - Source: dev.to / 2 months ago
  • Outgrowing Postgres: Handling increased user concurrency
    A caching layer using popular in-memory databases like Redis or Memcached can go a long way in addressing Postgres connection overload issues by being able to handle a much larger concurrent request load. Adding a cache lets you serve frequent reads from memory instead, taking pressure off Postgres. - Source: dev.to / 3 months ago
  • API Caching: Techniques for Better Performance
    Memcached — Free and well-known for its simplicity, Memcached is a distributed and powerful memory object caching system. It uses key-value pairs to store small data chunks from database calls, API calls, and page rendering. It is available on Windows. Strings are the only supported data type. Its client-server architecture distributes the cache logic, with half of the logic implemented on the server and the other... - Source: dev.to / 7 months ago
  • story of upgrading rails 5.x to 7.x
    The app depends on several packages to run, so I need to install them locally too. I used a combination of brew and orbstack / docker for installing packages. Some dependencies for this project are redis, mongodb and memcache. - Source: dev.to / 8 months ago
View more

GraphQL Cache mentions (4)

  • What are the Differences between GQL and REST?
    'id' data type and field to help support caching: https://graphql.org/learn/caching/. Source: over 2 years ago
  • GraphQL Is a Trap?
    > Take a look at this. I repeat: client-side caching is not a problem, even with GraphQL. The technical problems regarding GraphQL's blockers to caching lies in server-side caching. For server-side caching, the only answer that GraphQL offers is to use primary keys, hand-wave a lot, and hope that your GraphQL implementation did some sort of optimization to handle that corner case by caching results. Don't take my... - Source: Hacker News / almost 3 years ago
  • GraphQL Is a Trap?
    > Checkout Relay.js: https://relay.dev/ Relay is a GraphQL client. That's the irrelevant side of caching, because that can be trivially implemented by an intern, specially given GraphQL's official copout of caching based on primary keys [1], and doesn't have any meaningful impact on the client's resources. The relevant side of caching is server-side caching: the bits of your system that allow it to fulfill... - Source: Hacker News / almost 3 years ago
  • Designing a URL-based query syntax for GraphQL
    This is clever! Can anyone help me understand how this lines up with the original value proposition of GraphQL? I was under the impression that the Big Idea behind GraphQL was, amongst other things, client-side caching[1]. I’m probably missing some nuance here, so bear with me: if your GraphQL client is caching properly, then what would this syntax give a developer that a URL query parameter parser couldn’t? [1]... - Source: Hacker News / almost 4 years ago

What are some alternatives?

When comparing memcached and GraphQL Cache, you can also consider the following products

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

Ehcache - Java's most widely used cache.

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

Apache Ignite - high-performance, integrated and distributed in-memory platform for computing and transacting on...

Aerospike - Aerospike is a high-performing NoSQL database supporting high transaction volumes with low latency.

Hazelcast - Clustering and highly scalable data distribution platform for Java