Usual PoC approach. Don't assume that, since it worked fine for others, it'll work for you too out of the box, even if use cases are very similar. One should learn it hands-on - no different from other critical infrastructure components. Review collected by and hosted on G2.com.

Acceleration of reads for frequently-used complex data Review collected by and hosted on G2.com.

Truly understand the purpose of redis in your implementation. It's so easy to get caught up in newer tools (ahem, buzzwords) through word of mouth, and I often see new users working with Redis without even fully understanding why, how they benefit, or what other (sometimes more appropriate) options are available. Review collected by and hosted on G2.com.

- Asynchronous task management

- Mostly realized that it was much more convenient to use redis and celery than anything else. Documentation and support is wide-ranging, and speed wasn't really a concern, so the out of the box solution worked just fine.

- Realized even more tasks that can be passed off to asynchronous workers once it was all up and running so well. Review collected by and hosted on G2.com.

I found myself spending a lot of time searching for a decent SSO solution that was small, worked well with Nginx, and was quick. Eventually I gave up on the search and wrote my own and used Redis as a data store.

When I was spending time designing the session mechanism, some problems that always came up were expiration and session validation. In the sign-in process, a user is assigned a session token that maps to a hash of data in Redis. During sign-in, the SSO solution takes advantage of Redis' TTL and EXPIRE features to implement the session expiration. Because of this, the code got an extreme amount more simplistic. As far as validation goes, since it somewhat fits hand-in-hand with expiration, if the key expired or doesn't exist in Redis, the session is destroyed and the client is redirected.

With my SSO project, I really realized the true power of Redis. Its power and flexibility has drastically reduced the amount of code I had to write to achieve my goals. Review collected by and hosted on G2.com.

Take a look at other key-value stores before setting your heart on Redis. Redis seems to be the standard, but there are some new players on the block. There are several options that may be more worth your time if you don't need Redis to be networked, or you need it to be embedded within your application.

Where Redis really shines is synchronizing states across instances, both on the same machine, and across machines with little configuration. Review collected by and hosted on G2.com.

We are experimenting with using it as a sort of backend for our authentication and authentication platform as a cookie store.

Redis is perfect for syncing data between several machines and for being a key-value store for auth tokens. It's also useful for synchronizing state between multiple machines that doesn't need to persist. I used this for load-balancing websockets between servers without requiring the user to access the same server for each request, which serves to make the system more stateless. Review collected by and hosted on G2.com.

It is useful to take sometime to evaluate the data structures and choose a model that allows for fastest query times. Glob style key searches are linear and can take a while if data is too large. Review collected by and hosted on G2.com.

Use case was storing realtime billing and content consumption data persisted for a week for a mobile based service. Redis enabled very fast write throughput on a large volume of streaming data. It also made modelling the realtime aspects of the system a lot simpler than anticipated, unlike an RDMS of straight forward key/value data store would have. The suite of data structures saved writing a lot of analytics code (aggregations) which translated naturally to Redis queries given how the data was written. Review collected by and hosted on G2.com.

If you are looking for an alternative to Mysql, Redis is not it. It cant cope with large databases which can't be retained in memory.

Redis is more of a short and sweet thing that can handle relatively small number of variables with high throughput and is easy to deploy. Review collected by and hosted on G2.com.

I am generally not a fan of heavy databases and didn't think I would actually need that at all, except when I needed - it was not because the data was large, but because it needed reads and writes from multiple processes running in two remote machines. I turned to Redis as I had heard that it is very simple to get started with and is really fast. And to my surprise, it really did work like a breeze.

For python projects, redis-py is the official redis client library and it mostly just maps from redis commands to methods, like get, set and hmgetall, but it also supports transactions and others.

Benefits -

The code went from supporting just one machine (variables in python) to N number of remote machines (via redis) in just one day. It became only a matter of installing redis-cli on all remote machines and reading the data off the master redis database. Review collected by and hosted on G2.com.

Redis is absolutely necessary solution in web development and I couldn't imagine modern application without it. It has "one command" installation and you will enjoy using it. Review collected by and hosted on G2.com.

We widely use Redis in web development. Our main use cases: key-value store for sessions data and fast queue for task workers. Review collected by and hosted on G2.com.

I would recommend setting this software up locally to start, installing the python client for it and toying around with it. It is very easy to get started with. Just watch the instance sizing if you are using Digital Ocean, AWS, etc as it likes the memory which greatly bumps the costs up. Review collected by and hosted on G2.com.

For the most part, we are storing jobs that software needs to run on it in a distributed fashion. It has been very easy to implement and easy to monitor. Review collected by and hosted on G2.com.

While the clustering support is not yet as strong as memcached, Redis has begun to focus there as is evident with Redis Cluster. Definitely look into Redis Cluster when considering Redis. Review collected by and hosted on G2.com.

We need a high-performance, distributed key-value cache. We immediately realized large benefits when Redis came to our database's rescue, off-loading unnecessary requests when data was unlikely to change. Review collected by and hosted on G2.com.

There are many types of databases today, and none of them is suitable to store all kinds of data. Take care when evaluating Redis isn't a good choice, because it is - perhaps your scenario isn't well suited for it only. Review collected by and hosted on G2.com.

I'm using it barely to cache session data, which is one of the simplest use cases of Redis. It's very easy to setup it in any application for caching and it's very fast when running in memory. Also, it helped me remove temporary data from my main database. Review collected by and hosted on G2.com.