ClickHouse vs Redis comparison

"We faced a challenge with deploying ClickHouse onto Kubernetes. Recently, we've been using ClickHouse Cloud, and the main issue is the high cost of the cloud service. The pricing isn't very competitive, especially for startups. I would instead buy a server and self-host if I have enough disk space. Besides that, ClickHouse has done very well, with clear goals and effective execution."

"It's easier to work with big data and calculations using the product."

"If you have a real-time basis, you should take a look at ClickHouse because it works on a vector database, and the querying is super fast compared to traditional databases."

"The best thing about the tool is that I can set it up on my computer and run queries without depending on the cloud. This is why I use it every day."

"ClickHouse is much faster than traditional databases like MySQL and MongoDB. Its column-row searching strategy makes it very efficient. With ClickHouse, we can manage multiple databases, automatically insert data from other databases and delete data as needed. It supports real-time query performance, allowing simultaneous data insertion and retrieval. ClickHouse has improved significantly over the past two years, adding more functions and queries, as well as top functionality."

"ClickHouse is a user-friendly solution that tries to be compatible with SQL standards."

"The tool is column-based and infinitely scalable."

"The tool's most valuable feature is a database. It supports portal APIs and offers good flexibility."

"The online interface is very fast and easy to use."

"The in-memory data makes it fast."

"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."

"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 use Redis mostly to cache repeated data that is required."

"The solution's technical support team is good...The solution's initial setup process was straightforward."

"The solution is fast, provides good performance, and is not too expensive."

"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."

"If you join our team, it should be easy for you to use ClickHouse, especially if you are a developer. However, you need to read the documentation and understand the problems you are trying to solve."

"There are some areas where ClickHouse could improve. Specifically, we encountered incompatibilities with its SQL syntax when migrating queries from MySQL or SQL to ClickHouse. This difference in details made it challenging to figure out the exact issues. Additionally, we faced difficulties due to the lack of a proper Django driver for ClickHouse, unlike MySQL, which Django supports out of the box."

"ClickHouse has its own concept of database triggers and doesn't support traditional database triggers."

"One issue is that you need persistent volumes. Otherwise, if one system goes down, you lose data in that cluster."

"We had a lot of troubles while deploying a whole cluster."

"There aren't too many improvements I'd suggest for ClickHouse as it covers all my needs. There are just a few technical issues. For example, sometimes, when you want to get unique values and use certain tables, they don't work as expected. But it's not a major problem."

"The aggregation capability is a valuable feature. It's highly efficient, allowing us to review entire transaction histories and user activities in the market. We've tried MongoDB, Postgres, MariaDB, and BigQuery, but ClickHouse is the most cost-efficient solution for collecting data at high speeds with minimal cost. We even used ClickHouse Cloud for a month, and it proved to be a great setup, especially for startups looking to handle big data. For example, if there is a need for 2-4 terabytes of data and around 40 billion rows with reasonable computing speed and latency, ClickHouse is ideal. Regarding the real-time query performance of ClickHouse, when using an API server to query it, I achieved query results in less than twenty milliseconds in some of my experiments with one billion rows. However, it depends on the scenario since ClickHouse has limitations in handling mutations. Additionally, one of ClickHouse's strengths is its compression capability. Our experimental server has only four terabytes, and ClickHouse effectively compresses data, allowing us to store large amounts of data at high speed. This compression efficiency is a significant advantage of using ClickHouse."

"Initially, I faced challenges integrating ClickHouse, particularly with inserting data from ActiveMQ, which caused duplicates. However, after adjusting the ClickHouse settings, the issue was resolved and there were no more duplicates."

"The initial setup took some time as our technical team needed to familiarize themselves with Redis."

"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."

"It's actually quite expensive."

"Sometimes, we use Redis as a cluster, and the clusters can sometimes suffer some issues and bring some downtime to your application."

"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 would prefer it if there was more information available about Redis. That would make it easier for new beginners. Currently, there is a lack of resources."

"The development of clusters could improve. Additionally, it would be helpful if it was integrated with Amazon AWS or Google Cloud."

"If we use a lot of data, it will eventually cost us a lot."

"ClickHouse has an open-source version, which is free to use and has almost all the features."

"If you have an in-house deployment on Kubernetes or something, it's going to be very cheap since you'll be managing everything."

"We used the free, community version of ClickHouse."

"The tool is free."

"ClickHouse Cloud is not expensive compared to other databases, costing a few dollars per month while providing fast performance."

"For pricing, if you use the self-hosted version, it would be free. Cloud services pricing would be an eight out of ten. I try to minimize costs but still have to monitor usage."

"The tool is open-source."

"We saw an ROI. It made the processing of our transactions faster."

"Redis is not an overpriced solution."

"Redis is an open-source solution. There are not any hidden fees."

"Redis is an open-source product."

"The tool is open-source. There are no additional costs."