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Highly scalable distributed cache
What do you like best about the product?
It's very easy to integrate and easy to scale. Rich in lot of Data Structure and Algorithm.
What do you dislike about the product?
Nothing such. I haven't faced any issue so far.
What problems is the product solving and how is that benefiting you?
We are using redis as a distributed cache. It's very easy to use and easy to scale. performance is also good.
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Best caching solution
What do you like best about the product?
I was able to easily build a key value data store using redis. Using the replication function of redis 3.0, we were able to respond effectively to failures. Redis is used for session management of applications. It is also used to centrally manage meta data.
What do you dislike about the product?
You should keep in mind that Redis's cache TTL operates in a sampling manner. If you need to process Expired Event of a large amount of data, CPU usage may increase.
What problems is the product solving and how is that benefiting you?
Used for DB query result cache. It was used as an application session store. It was also used for application development based on TTL Expired Event.
Perfect for real-time operations
What do you like best about the product?
How it handles large amounts of event subscriptions quickly; it contains useful data structures which allow for easy querying
What do you dislike about the product?
Lack of documentation; debugging can be onerous
What problems is the product solving and how is that benefiting you?
Handling a rapid influx and broadcast of WebRTC events with multiple subscribers. We have realised it's very quick and scaleable
It help us to improve the performance.
What do you like best about the product?
Easy Implementation with multiple technologies Java, Node etc.
What do you dislike about the product?
Improve documentation with more example.
What problems is the product solving and how is that benefiting you?
We are using Redis as middleware in NodeJS to save calls on the Database and improve performance
Does the Job Pretty Good
What do you like best about the product?
Fast Key Value Hash operations.
Slow Latency.
Expired Keys
Cloudwatch Integration.
Slow Latency.
Expired Keys
Cloudwatch Integration.
What do you dislike about the product?
Single Threaded. You won't benefit from having multi-core CPUs.
Lack of having a GUI client
Maybe lack of good training materials. I always find difficulty finding answers. It's either out of date or takes a lot of time to get answers to what I want
Lack of having a GUI client
Maybe lack of good training materials. I always find difficulty finding answers. It's either out of date or takes a lot of time to get answers to what I want
What problems is the product solving and how is that benefiting you?
Mostly caching. We used to cache the locations of the sales users in real time inside Redis.
Moderate Experience
What do you like best about the product?
Sharing cache between microservices with high performance
What do you dislike about the product?
I haven't yet experienced any downsides of using Redis
What problems is the product solving and how is that benefiting you?
Redis helped me solve the shared cache problem and Pub/Sub communication between my microservices
used redis with different apps including shared caching and as message broker
What do you like best about the product?
the best about redis is the persistent volumes and how much it is fast to save and retrieve data . also publishing and subscribing message broker which i use as events is so helpful.
What do you dislike about the product?
it is intenteded to solve various problems , cant see any downsides.
What problems is the product solving and how is that benefiting you?
the best solution comes with redis, is when the memory cache is no more beneficial between different apps. here where the strong point of redis appears, rather than no fear of any app shutdown since all the volumes are persistent.
A Good Distributing in Memory Caching Service
What do you like best about the product?
A lot of variation in data types.
Perfect for read-intensive applications.
Supports many programming languages.
The replication feature is very useful.
Perfect for read-intensive applications.
Supports many programming languages.
The replication feature is very useful.
What do you dislike about the product?
Sometimes the documentation is very clear
The data querying could be improved
The data querying could be improved
What problems is the product solving and how is that benefiting you?
We solved many problems such as
- Sharing of cache between multiple microservices
- We usually put the data read-intensive records in the cache for example the tending news for news website
- Sharing of cache between multiple microservices
- We usually put the data read-intensive records in the cache for example the tending news for news website
Best Cache store
What do you like best about the product?
We used it save the reservation data in cache for faster ii experience.
What do you dislike about the product?
There is nothing which I disliked as of now.
What problems is the product solving and how is that benefiting you?
Slow read from rdbms where caching the reservation data helps in quick response time.
Scaled our Php Systems 100x and turned a 1 hour lag ELK cluster into realtime.
What do you like best about the product?
Its an all in one Utility Pack that uses very little memory on startup. I have used it for storing XML hotel master data as Tables rows. While caching inventory as Key/Values and as a Broker to improve performance for the ELK stack. The distributed cache makes it even faster when using multiple data-centers across continents.
What do you dislike about the product?
It has a very old pre-compiled version for Windows.
What problems is the product solving and how is that benefiting you?
Our greatest challenge was Session replication & Session storage for our LAMP Php websites. We were subject to use sticky session based Load-balancing, but as soon as we realized Redis can store Php sessions, we started focusing on development instead of platform scaling. We increased our site/hits by 100x times and sales by 10x within a short period. We also used Redis as a broker for the ELK stack to reduce lag time to almost realtime.
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