Redis vs RethinkDB: What are the differences?
Developers describe Redis as "An in-memory database that persists on disk". Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets. On the other hand, RethinkDB is detailed as "JSON. Scales to multiple machines with very little effort. Open source". RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.
Redis belongs to "In-Memory Databases" category of the tech stack, while RethinkDB can be primarily classified under "Databases".
"Performance" is the top reason why over 842 developers like Redis, while over 46 developers mention "Powerful query language" as the leading cause for choosing RethinkDB.
Redis and RethinkDB are both open source tools. Redis with 37.1K GitHub stars and 14.3K forks on GitHub appears to be more popular than RethinkDB with 22.3K GitHub stars and 1.73K GitHub forks.
reddit, Instacart, and Slack are some of the popular companies that use Redis, whereas RethinkDB is used by miDrive, Runbook, and The Control Group. Redis has a broader approval, being mentioned in 3239 company stacks & 1732 developers stacks; compared to RethinkDB, which is listed in 37 company stacks and 25 developer stacks.
What is Redis?
What is RethinkDB?
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We initially chose RethinkDB because of the schema-less document store features, and better durability resilience/story than MongoDB In the end, it didn't work out quite as we expected: there's plenty of scalability issues, it's near impossible to run analytical workloads and small community makes working with Rethink a challenge. We're in process of migrating all our workloads to PostgreSQL and hopefully, we will be able to decommission our RethinkDB deployment soon.
I use Redis because, based on the case studies I have reviewed, it appears to be the most performant cache database for my Django projects. The ease of configuration and deployment is also a big plus.
Using both higher level view caching as well as low-level QuerySet caching with Redis has allowed me to improve HTTP request times by an order of magnitude.
Redis is a good caching tool for a cluster, but our application had performance issues while using Aws Elasticache Redis since some page had 3000 cache hits per a page load and Redis just couldn't quickly process them all in once + latency and object deseialization time - page load took 8-9 seconds. We create a custom hybrid caching based on Redis and EhCache which worked great for our goals. Check it out on github, it's called HybriCache - https://github.com/batir-akhmerov/hybricache.
Redis is used for storing all ephemeral (that's data you don't necessarily want to store permanently) user data, such as mapping of session IDs (stored in cookies) to current session variables at Cloudcraft.co. The many datastructures supported by Redis also makes it an excellent caching and realtime statistics layer. It doesn't hurt that the author, Antirez, is the nicest guy ever! These days, I would be really hard pressed to find any situation where I would pick something like Memcached over Redis.
Trello uses Redis for ephemeral data that needs to be shared between server processes but not persisted to disk. Things like the activity level of a session or a temporary OpenID key are stored in Redis, and the application is built to recover gracefully if any of these (or all of them) are lost. We run with allkeys-lru enabled and about five times as much space as its actual working set needs, so Redis automatically discards data that hasn’t been accessed lately, and reconstructs it when necessary.
The UI has message inbox that is sent a message when you get a new badge, receive a message, significant event, etc. Done using WebSockets and is powered by redis. Redis has 2 slaves, SQL has 2 replicas, tag engine has 3 nodes, elastic has 3 nodes - any other service has high availability as well (and exists in both data centers).
Redis makes certain operations very easy. When I need a high-availability store, I typically look elsewhere, but for rapid development with the ability to land on your feet in prod, Redis is great. The available data types make it easy to build non-trivial indexes that would require complex queries in postgres.
I use Redis for cacheing, data storage, mining and augmentation, proprietary distributed event system for disparate apps and services to talk to each other, and more. Redis has some very useful native data types for tracking, slicing and dicing information.
High-speed update-aware storage used in our region server infrastructure; provides a good middle layer for storage of rapidly modified information.
Main database, using it in multiple datacenters in an active-active configuration.