ClickHouse vs. Valentina

ClickHouse delivers exceptional speed and performance, positioning it as the top choice for managing large-scale analytical workloads. With a bunch of built-in functions, it empowers analysts to extract maximum insights from data effortlessly. If your scenario is to deal with analytical questions, then ClickHouse is for you, but if you are looking into a transactional database, that's not the case; even their table engines are not made for this.

Incentivized

If you have to manage a lot of different databases from different vendors, you could do well by standardizing on this product. It checks all the boxes for a proper database management studio. You would only have to learn one product to manage them all. However, if you are looking to find a good product for a single database vendor, you might be better off finding a tool that was designed specifically for that vendor product.

Incentivized

• Their MergeTree table engine provide impressive performance for data insert in bulk
• Not only data insert but also the way MergeTree engine uses Primary Keys to sort the data and perform data skipping based on the granules its also their secret for ridiculous fast queries
• Data compression its also great
• They provide especial table engines that allow you to read data directly from other sources like S3
• Since its written with C++ you have very granular data types and especial ones like enum, LowCardinality and etc, they save you a lot of storage since are stored as integer values
• ClickHouse functions besides the ones that respect ANSI Standards are also awesome and useful

Incentivized

• Foreign Key Constraint data viewer! This was a tremendously helpful feature that not many other products have. Just pick a constraint and see the data in the child tables! No setup required!
• Supports any and every database imaginable.

Incentivized

• Avro data manipulation
• Kafka consistency
• DDL operations errors (by replica configuration)

Incentivized

• Somewhat laggy performance. Boot up speed was on the slow side and connecting to our database servers was also a little slower than other products.
• User interface can be a little clunky. Instead of the usual tree view of servers, databases, and schemas, you are presented with lists that you click on and get new windows to pick the new list of data from. Not organized efficiently.

Incentivized

ClickHouse was not compared to them as a competitor but as the ideal partner to complete an information analysis system, providing users with the most complete and efficient tools. Therefore, in this case it was considered that it would be the ideal candidate due to its characteristics compared to the other competitors.

Incentivized

Compared to Microsoft's SQL Management Studio, Valentina studio was comparable, just harder to get used to in the UI department. It ran slightly slower than other products but did save some time with neat features they baked into the product. However, in using DBeaver Community and DBForge Studio for PostgreSQL from Devart, we found different products that the team ultimately decided to use. DBeaver has all of the features we needed most (minus the constraint data viewer) and a more intuitive UI that we were used to. DBForge Studio for PostgreSQL has a very standard Windows look and feel and lacks some features, like database/table designers, but makes up for those shortcomings in the much easier filtering and sorting options right in the data grids. You can even write a query and edit the data returned, which is something we don't see in many of these tools. Our team ultimately settled on the developers using DBeaver and the support team that needs data viewing/editing capabilities using DBForge Studio.

Incentivized

• Queries that used to take more than 2 minutes now take less than 1 second
• Possibility to analyze use cases in real time (before was impossible)
• The applications are more complete and the users decisions are better

Incentivized

• It saved time in some areas of finding child data by not having to write queries to find it.
• The user interface caused some extra training for some users and ultimately caused them to not like using it.

Incentivized