External reviews are not included in the AWS star rating for the product.
I use Redis mostly to cache repeated data that is required. If I'm using a user wallet address, I don't need to call it all the time from the database. I do the cache using the solution.
The solution allows you to create a message of application publishing and messaging the application in other services. It helps a lot when I work with the microservice architecture.
I have been using Redis for four years.
I haven’t faced any stability issues with the solution.
I have never faced any issues with the solution’s scalability.
The solution is easy to set up and has very clear documentation.
To deploy Redis, you need knowledge about JavaScript, programming, and how data structures are stored. It takes around five to ten minutes to deploy the solution.
With Redis, I can create lists and key-value pairs. The solution also provides many features for storing data in cache. Storing data in memory using Redis is faster than using traditional databases like Postgres or MySQL.
If you are communicating with the services, you can use the solution's Pub/Sub capabilities to send messages, store data in cache, and share it with other microservices. The solution's data persistence model has greatly benefited our resilience, especially when storing any key-value pair.
You can install the solution on the local machine or cloud servers like AWS or Google Cloud. I would recommend Redis to other users.
Overall, I rate the solution a nine out of ten.
Our organization's main use case for Redis is to store and load static content for our multi-client products.
The best thing about Redis is its ability to handle large amounts of data without frequently hitting the database. You can store data in temporary memory, especially for high-volume data.
The tool should improve by increasing its size limits and handling dynamic data better. We use the client ID or associate it with a key for static content. The solution will not be easy for a beginner. Unless you understand SQL data, it will be difficult to understand and use Redis. It also needs to be user-friendly.
I haven't contacted technical support yet.
The tool is open-source. There are no additional costs.
If you have a large amount of non-dynamic data that needs to be delivered to the client, you should use Redis. I don't think that it will support AI initiatives since it doesn't support continuous data. I rate the overall solution a seven out of ten.
We use the solution as a caching layer.
The ability to fetch and save data quickly is valuable. We can fetch data within milliseconds. The tool provides data structure capabilities. It also provides geolocation search and JSON search capabilities. The performance is very good. Redis can save each internal transaction to the file system. It helps us handle persistence in our storage.
The product's main purpose is caching, even though the vendor says we can also use it as a persistent database. If we use a lot of data, it will eventually cost us a lot. The tool is single-threaded. It doesn't support many data models. We only have key-value, hash, and JSON.
I have been using the solution for more than ten years.
The tool is stable.
The tool is easy to scale. We can add additional storage, and it will scale easily. We have millions of end users. We are an enterprise-level organization.
The product provides excellent support.
Positive
The deployment is easy. The deployment takes a couple of hours. One engineer can deploy the tool. We can fully manage the tool as SaaS with low maintenance. If we want to deploy it in our own environment, we must be more aware of changes and monitoring. Since I'm using the caching layer, we must choose the correct mode to save and fetch the data optimally. It is complicated to understand which feature or model we must use.
Eventually, we need to manage caching. If we manage on our own, it will take a lot of developer resources, infrastructure, and environmental resources. So, it is better to use Redis. The ROI is better.
We pay a yearly fee, but we pay according to the usage.
I also work with PostgreSQL, MySQL, Elasticsearch, Cassandra, and Splunk. Redis provides efficient caching and performance. The other solutions have persistent storage functionality. If I want persistence, I would use the other tools. If I need high performance, I would use Redis.
We must understand our system needs and pick the correct data structure in Redis to support it most efficiently. Overall, I rate the tool an eight out of ten.
We use it primarily for real-time applications. In our web application, we added a feature where hundreds of people could play a quiz in real time.
Instead of using traditional databases like SQL, we implemented Redis to make everything happen in real time – all those quick calculations, data hashing for easy retrieval, and so on.
It was a live quiz feature, so Redis helped a lot. I also use Redis for caching and similar general use cases.
It improved the performance. For example, data structures like hashmaps in Redis make it a very fast database – much faster than traditional SQL databases. It can perform at significantly higher speeds. Latencies are very low. Our primary focus wasn't on saving money but on improving performance for that specific feature.
So, performance has been the key improvement. Every calculation happened in real time. It improved the performance 10X.
In our company, we have limited resources, so we can't manage the database ourselves. We use services from Azure for that. So, Redis integrates well with those services.
We use Azure Cache for Redis.
It performs much better than traditional databases. Our calculations happen in real-time, which was crucial for that quiz feature.
The price could be better.
I have been using it for more than two years.
It has been a reliable product for us.
It's been working very well for us. Since our scale isn't huge, it's able to handle our needs without issues.
I've also worked with PostgreSQL, Cassandra, MySQL, and Elasticsearch.
It's tough to find a direct competitor because Redis, Cassandra, PostgreSQL, and Elasticsearch all serve different purposes. Cassandra excels when you structure tables according to your requirements upfront. It offers fast reads. However, the Cassandra Query Language (CQL) isn't as flexible as SQL – there are no joins, for example. It is a very restricted query language. So, we need to carefully design your database tables with future data needs in mind.
Redis is better tested and is used by large companies. I haven't found a direct alternative to what Redis offers. Plus, there are a lot of support and learning resources available, which help you use Redis efficiently.
It's actually quite expensive compared to SQL since Redis uses a system's main RAM, which is costly. And memory can be limited.
We opt for a dedicated server.
Overall, I would rate the solution an eight out of ten. It's been very stable so far and performs well within our system.
I would recommend it, but I would also highlight the cost factor as something to consider.
I have been using a specific infrastructure. We use it primarily for customer service.
It makes operations more efficient. The information processing is very fast, and very responsive. It's all about the technology.
The only thing is the lack of a GUI application. There was a time when we needed to resolve an issue in production. If we had a GUI, it would have been easier. But no one provided a GUI, or maybe we didn't request it. I'm not sure. We just make use of it.
My experience with this product has been very good.
It's been very stable. I would rate the stability a ten out of ten.
We saw an ROI. It made the processing of our transactions faster. So there are some details we get, like customer contract details, customer details, customer ID, there are so many details for that. So we get it from Redis, which makes it faster.
I would rate it an eight out of ten.
I would recommend to explore this product as it's gonna make the work easy.
We use Redis for caching and to improve the speed of the database.
The product offers fast access to my database.
I have been working with the product since 2022.
Since implementing the product, we have experienced stability in our applications.
The solution is scalable.
The initial setup took some time as our technical team needed to familiarize themselves with Redis. Once they gained expertise, the deployment process became straightforward and was completed within a month and a half. A seven-member team helped with the deployment.
Redis is an open-source product.
I rate the product an eight out of ten.
Sometimes, Redis is used as a cache and sometimes as the main database.
Redis is a simple, powerful, and fast solution.
Sometimes, we use Redis as a cluster, and the clusters can sometimes suffer some issues and bring some downtime to your application.
I have been using Redis for three years.
I rate Redis a seven or eight out of ten for stability.
In our team, around 20 to 25 engineers are using the solution.
I rate Redis a nine or ten out of ten for scalability.
The solution's technical support team was quite knowledgeable and fast.
Positive
We previously used other solutions like DynamoDB, Elasticsearch, and Postgres for different use cases. We switched to Redis because maintaining the cluster for Elasticsearch was very complex and a lot of work. Also, the other solutions were very, very expensive.
The solution’s initial setup is easy.
Since we're using the AWS self-managed version, Redis can be deployed very fast if you go through the console. If you do an infrastructure, its setup will take longer. But if you just want to play with it and set it up quickly, it can be done in 10 to 15 minutes or less.
The solution's pricing is good compared to other databases doing the same thing. It might be cheaper to use Redis in some cases and not in others. Redis is not an overpriced solution.
Redis is deployed on-cloud in our organization.
When it started, Redis had a very simple structure, but now it has a lot of powerful data structures. Users should investigate because they can use other things for their data structure. Redis has more new use cases. Users must consider that Redis is single-threaded, which might take a toll on them when they write to Redis. This might be an issue if you need very high throughput with writes.
Overall, I rate Redis a nine out of ten.