I used Redis for a one-time implementation while working on a college project. I implemented it locally on a machine and used it for a vector search.

Since it was a university project, it helped in providing a stable and efficient solution for my project needs. This enabled me to complete the project successfully and pass an exam.

Redis is stable, provides consistent results, and is fast. It is particularly efficient for cloud-based storage and operations.

Redis could improve its efficiency in handling locally stored data, not just Amazon Cloud or Google Cloud. It would be helpful if Redis could provide a one-stop solution for all data varieties, which would improve the integrity between different databases.

I used Redis for about a day for the implementation.

Redis is definitely a stable product. It provided accurate and consistent results without any issues.

Redis is a highly scalable product, especially since it effectively handles cloud-based storage, which is the most scalable option.

I did not communicate with the technical support team, so I cannot provide a rating for customer service.

Positive

I also used Firest for my project and found it to be more suitable for my specific use case.

The initial setup was very easy. The only requirement was to change the syntax from Redis to Firest and vice versa.

I completed the implementation all by myself without needing any additional help.

I used the free, open-source version of Redis, so I did not incur any costs. For personal use, a lower price is always better.

I evaluated and used Firest and several other databases for my project, including Crontabee and Cosmodb.

Redis is beneficial for specific usage and domains. If Redis can handle various data types efficiently, it would become a comprehensive solution for any use case, potentially topping other databases. Its consistent results and free, open-source nature make it a solid choice.

I'd rate the solution eight out of ten.

In the past, I used Redis as a cache, and currently, I'm using it as a messaging system.

Redis is pretty fast compared to others, making it a reliable choice. It's much more reliable and helps with our message broker functionalities.

Redis is a single thread, which is one of the key features I like. Redis is also pretty fast, and many of our use cases are satisfied with its single-threaded nature. This feature helps us manage concurrency effectively.

I don't think there's any room for improvement as it's been good for large-scale use and large datasets.

I have been using Redis for almost three years now.

I haven't faced any issues from a performance, outage, or availability point of view. It's good.

It's very easy to scale up and scale down. I'd say it's highly scalable.

I didn't get a chance to interact with their support team.

Positive

Use Redis wisely because it is a single-threaded tool. There was an issue we faced in the past where a query was not optimized, which impacted performance significantly.

I've used Redis mainly to improve application performance through caching. I've also used it as a small project broker and an external lock mechanism. I used it in previous companies. 

What I like best about Redis is its fast and easy use. It has interesting algorithms like HyperLogLog and provides useful features. It's also good for implementing scalable rate limiting.

I have been using the solution for eight years. 

I haven't faced any stability issues. 

I rate the tool's scalability an eight out of ten. 

Redis is an open-source solution. 

I rate the overall solution a ten out of ten. 

I use Redis for data deduplication or identifying duplicate records I receive. I have a very basic usage with Redis, where I insert a key value record.

The solution is fast, provides good performance, and is not too expensive. Although installing it locally would probably be cheaper, I don't want the hassle. For the functionality I need, Redis gives me what I want at the moment.

The solution's pricing for a local installation is very expensive.

I have been using Redis for three years.

I haven’t faced any issues with the solution’s stability.

Azure allows Redis to scale. If I want, I can increase the resources allocated for this service.

I'm using the solution as an Azure cloud service with no installation involved.

The solution does what I need, and I have no issues with it. Since I didn't install Redis and don't need to maintain it, the service saves me a lot of time.

Overall, I rate the solution ten out of ten.

I'm the only user utilizing Redis in my company, as my platform is relatively new and has around fifty users. However, in my previous role at Profit Clicks, we had approximately ten thousand users. We utilized a combination of databases, including Redis, MongoDB, and MariaDB. We needed to handle push notifications for our users, sending them three times a day, and managing a large volume of notifications efficiently was crucial. Redis played a role in managing this workload.

I find Redis valuable primarily for its caching capabilities, particularly in handling cache requests effectively. Its simplicity in managing key-value pairs for caching is one of its strengths, making it a preferred choice over more complex databases like MongoDB for specific use cases. However, I haven't explored Redis extensively for managing complex data structures beyond caching, as MongoDB might be more suitable for such scenarios.

There are some features from MongoDB that I would like to see included in Redis to enhance its overall efficiency, such as the ability to perform remote behaviour. MongoDB is more efficient in handling updates than deletions and is quicker in processing updates, but it can be slower regarding deletions. This can sometimes pose a challenge, especially when dealing with large datasets or frequent data manipulations that involve deletions. In such cases, I often rewrite columns or update values instead of directly deleting data, as it can be more efficient.

I have been working with Redis for the last year approximately.

Redis is stable and works well without any issues on my end. I occasionally encounter problems with MongoDB because MongoDB has a very different stack.

It is a scalable solution.

Redis requires occasional maintenance, but it is generally a low-maintenance solution and is straightforward to manage. I haven't encountered any difficulties or downtime after updates, as Redis is robust and concise.

I haven't explored AI-driven initiatives yet, but they are on my road map. I would recommend Redis for all kinds of caching and message brokering needs. It's a reliable and straightforward solution.

Overall, I would rate Redis ten out of ten.

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.