Perfect solution for caching needs. If you have a bottleneck due to frequent data access to your database, then Redis can really help you by diverting those traffic away from your database. Its key/value pair structure also makes data lookup very efficient, providing excellent performance.
Riak is very good if you need a resilient data store that can handle large amounts of documents very fast. If you have 1,000,000 documents and need to execute complex queries, it is great. Riak's SOLR engine is fast, however if you have extremely high amount of queries in a very limited time range, it can fail in a bad way.
Easy for developers to understand. Unlike Riak, which I've used in the past, it's fast without having to worry about eventual consistency.
Reliable. With a proper multi-node configuration, it can handle failover instantly.
Configurable. We primarily still use Memcache for caching but one of the teams uses Redis for both long-term storage and temporary expiry keys without taking on another external dependency.
Fast. We process tens of thousands of RPS and it doesn't skip a beat.
Redis is super fast but it comes with a cost. Whole dataset resides in RAM. So it can be costly as primary memory is more costly, then secondary ones.
Persistence issues: To achieve it, Redis uses a memory dump to create a persistence snapshot, that's cool. But it requires some Linux Kernel tweaking to avoid performance degradation while the Redis server process is forking. This further causes latency.
Master-slave structure side effect: Master-slave architecture comes with its own side effects. Please note that there will be only one master with multiple slaves for replication. All writing goes to the master, which creates more load on the master node. So, when the master goes down, the whole architecture does.
We will definitely continue using Redis because: 1. It is free and open source. 2. We already use it in so many applications, it will be hard for us to let go. 3. There isn't another competitive product that we know of that gives a better performance. 4. We never had any major issues with Redis, so no point turning our backs.
Riak works great for our use case but the fact that deletes seem to resurrect is a real issue for us. Unless we can get this solved, we'll continue to look at other products to see if our use case fits. Otherwise Riak is a great product and it fits our use case 95%. We have found work arounds to the remaining 5%.
It is quite simple to set up for the purpose of managing user sessions in the backend. It can be easily integrated with other products or technologies, such as Spring in Java. If you need to actually display the data stored in Redis in your application this is a bit difficult to understand initially but is possible.
The support team has always been excellent in handling our mostly questions, rarely problems. They are responsive, find the solution and get us moving forward again. I have never had to escalate a case with them. They have always solved our problems in a very timely manner. I highly commend the support team.
Despite Basho going bankrupt and the project becoming fully open-source, community support is reasonably good, albeit a little slow at times. Paid enterprise-grade support is also available from former Basho engineers but the same company also contributes to the community support for free for basic questions or specific knowledge areas.
UI isn't that great compared to the other competitors. The management of our memcached cluster was becoming pretty complicated as the application grew in size. Redis is a much better option compared to memcached. Redis is bit unreliable compared to the alternative RabbitMQ especially when it needs to be integrated with Celery.
MongoDB seems to have copied a lot of functionality from Riak. This may be because MongoDB hired a number of former Basho engineers when Basho went bankrupt. That said, the new functions added to Riak after it became open source have successfully differentiated itself from MongoDB.
Amazon S3 is a nice tool but when you are at significant scale with regionally specific data (joys of GDPR), it's much easier to keep it in house and Riak CS lets you do exactly that. All you need to do is point your application at Riak CS instead of Amazon S3 and it just works as if nothing has changed.
When we evaluated against Cassandra, we found the tools available did not match our needs at the time.
Existing tools like Redisson that were built over Redis reduced dev time in solving challenging problems, which had a positive impact on ROI.
We initially misused Redis for persistent storage which had a negative impact on ROI because we were paying a lot for inactive users.
The increased performance we achieved using Redis in areas like locking helped us improve the performance of our system reducing the likelihood of system timeouts.
