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GraphQL Cache VS Redis ™

Compare GraphQL Cache VS Redis and see what are their differences

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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.

Redis logo Redis

Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
  • GraphQL Cache Landing page
    Landing page //
    2023-08-29
  • Redis Landing page
    Landing page //
    2022-10-19

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache and message broker. It supports data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes with radius queries and streams. Redis has built-in replication, Lua scripting, LRU eviction, transactions and different levels of on-disk persistence, and provides high availability via Redis Sentinel and automatic partitioning with Redis Cluster.

GraphQL Cache features and specs

No features have been listed yet.

Redis features and specs

  • Performance
    Redis is an in-memory data store, which allows it to provide extremely fast read and write operations. This makes it ideal for applications requiring real-time interactions.
  • Data Structures
    Redis offers a variety of data structures, such as strings, hashes, lists, sets, and sorted sets. This flexibility helps developers manage data more efficiently in different scenarios.
  • Scalability
    Redis supports horizontal scalability with features like clustering and partitioning, allowing for easy scaling as your application grows.
  • Persistence
    Though primarily an in-memory store, Redis provides options for data persistence, such as RDB snapshots and AOF logs, enabling data durability across reboots.
  • Pub/Sub Messaging
    Redis includes a built-in publish/subscribe messaging system, which can be used to implement real-time messaging and notifications.
  • Simple API
    Redis has a simple and intuitive API, which can speed up development time and make it easier to integrate Redis into various application stacks.
  • Atomic Operations
    Redis supports atomic operations on data structures, reducing the complexity of concurrent programming and making it easier to maintain data consistency.

Possible disadvantages of Redis

  • Memory Usage
    Being an in-memory data store, Redis can become expensive in terms of memory usage, especially when working with large datasets.
  • Data Persistence Limitations
    While Redis offers data persistence, it is not as robust as traditional databases. There can be data loss in certain configurations, such as when using asynchronous persistence methods.
  • Complexity in Scaling
    Although Redis supports clustering, setting up and managing a Redis cluster can be complex and may require significant DevOps expertise.
  • Single-threaded Nature
    Redis operates on a single-threaded event loop, which can become a bottleneck for certain workloads that could benefit from multi-threading.
  • Limited Query Capabilities
    Compared to traditional relational databases, Redis offers limited querying capabilities. Complex queries and joins are not supported natively.
  • License
    As of Redis 6 and higher, the Redis modules are under the Server Side Public License (SSPL), which may be restrictive for some use cases compared to more permissive open-source licenses.

GraphQL Cache videos

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Redis videos

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Improve your Redis developer experience with RedisInsight, Redis Labs

More videos:

  • Review - What is Redis? | Why and When to use Redis? | Tech Primers
  • Review - Redis Enterprise Overview with Yiftach Shoolman - Redis Labs
  • Review - Redis Labs "Why NoSQL is a Safe Bet"
  • Review - Redis system design | Distributed cache System design
  • Review - What is Redis and What Does It Do?
  • Review - Redis Sorted Sets Explained

Category Popularity

0-100% (relative to GraphQL Cache and Redis)

GraphQL Cache

Redis

Databases
1 1%
Databases
99% 99
NoSQL Databases
2 2%
NoSQL Databases
98% 98
Key-Value Database
2 2%
Key-Value Database
98% 98
GraphQL
100 100%
GraphQL
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 GraphQL Cache and Redis

GraphQL Cache Reviews

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Redis Reviews

Redis Alternative for App Performance | Gigaspaces
Redis offers a RESTful API for accessing data stored within its in-memory technology data structures. This API provides a simple and efficient way to interact with Redis, enabling developers to leverage its capabilities seamlessly in their applications. Developers also need to manage the Redis cached data lifecycle, it’s the application responsibility to store the data &...
Source: www.gigaspaces.com
Are Free, Open-Source Message Queues Right For You?
A notable challenge with Redis Streams is that it doesn't natively support distributed, horizontal scaling. Also, while Redis is famous for its speed and simplicity, managing and scaling a Redis installation may be complex for some users, particularly for persistent data workloads.
Source: blog.iron.io
Redis vs. KeyDB vs. Dragonfly vs. Skytable | Hacker News
1. Redis: I'll start with Redis which I'd like to call the "original" key/value store (after memcached) because it is the oldest and most widely used of all. Being a long-time follower of Redis, I do know it's single-threaded (and uses io-threads since 6.0) and hence it achieves lesser throughput than the other stores listed above which are multi-threaded, at least to some...
Source: news.ycombinator.com
Memcached vs Redis - More Different Than You Would Expect
Remember when I wrote about how Redis was using malloc to assign memory? I lied. While Redis did use malloc at some point, these days Redis actually uses jemalloc. The reason for this is that jemalloc, while having lower peak performance has lower memory fragmentation helping to solve the framented memory issues that Redis experiences.
Source: engineering.kablamo.com.au
Top 15 Kafka Alternatives Popular In 2021
Redis is a known, open-source, in-memory data structure store that offers different data structures like lists, strings, hashes, sets, bitmaps, streams, geospatial indexes, etc. It is best utilized as a cache, memory broker, and cache. It has optional durability and inbuilt replication potential. It offers a great deal of availability through Redis Sentinel and Redis Cluster.
Source: www.spec-india.com

Social recommendations and mentions

Based on our record, Redis seems to be a lot more popular than GraphQL Cache. While we know about 218 links to Redis, we've tracked only 4 mentions of GraphQL Cache. 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.

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 / about 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 / about 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 / about 4 years ago

Redis mentions (218)

  • Cache Invalidation: The Silent Performance Killer
    Picture this: you've just built a snappy web app, and you're feeling pretty good about it. You've added Redis to cache frequently accessed data, and your app is flying—pages load in milliseconds, users are happy, and you're a rockstar. But then, a user updates their profile, and… oops. The app still shows their old info. Or worse, a new blog post doesn't appear on the homepage. What's going on? Welcome to the... - Source: dev.to / 29 days ago
  • Feature Comparison: Reliable Queue vs. Valkey and Redis Stream
    Valkey and Redis streams are data structures that act like append-only logs with some added features. Redisson PRO, the Valkey and Redis client for Java developers, improves on this concept with its Reliable Queue feature. - Source: dev.to / about 1 month ago
  • Finding Bigfoot with Async Generators + TypeScript
    Of course, these examples are just toys. A more proper use for asynchronous generators is handling things like reading files, accessing network services, and calling slow running things like AI models. So, I'm going to use an asynchronous generator to access a networked service. That service is Redis and we'll be using Node Redis and Redis Query Engine to find Bigfoot. - Source: dev.to / about 2 months ago
  • Caching Isn’t Always the Answer – And Here’s Why
    Slap on some Redis, sprinkle in a few set() calls, and boom—10x faster responses. - Source: dev.to / about 2 months ago
  • RisingWave Turns Four: Our Journey Beyond Democratizing Stream Processing
    Real-time serving: Many push processed data into low-latency serving layers like Redis to power applications needing instant responses (think fraud detection, live recommendations, financial dashboards). - Source: dev.to / 2 months ago
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What are some alternatives?

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

WunderGraph - Save 2-4 weeks / 90% of the code building web apps by automating API integrations and security.

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

Ehcache - Java's most widely used cache.

ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.

EdgeDB - EdgeDB is a next-generation graph-relational database that lets you easily build flexible, scalable applications in real-time.

Apache Cassandra - The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.

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