ClickHouse vs. Grist

The most important thing when using ClickHouse is to be clear that the scenarios in which you want to use it really are the right ones. Many users think that when a database is very fast for a specific use case, it can be extrapolated to other contexts (most of the time different) in which a previous analysis has not been carried out.

ClickHouse is an analytical database, as such, it should be used for such purposes, where the information is stored correctly, the data volumes are really large and the queries to be performed are not the typical traditional queries on several columns with multiple aggregations. ClickHouse is not the solution for this.

On the other hand, if your case is not one of the above, it is quite possible that ClickHouse can help you. Where ClickHouse shines is when you are looking for aggregation over a particular column in large volumes of data.

Incentivized

This is well suited to someone (or a team) who are technically minded and have a dataset that they need to be able to use in many ways. It's less appropriate for a team who isn't technically minded and/or don't have the data they need to manipulate. It would be useful for things that you could use a database or spreadsheet for such as CRM, Advertising database, Business tracking, Health tracking etc.

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

• Provides amazing customer service, help, examples, and explains what they are having you do
• The layout is easy

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

Incentivized

• Making the user permissions more obvious on how to use them - They are highly adaptable, but hard to understand how to use them
• Small changes such as auto colouring the choices/toggles options and being able to edit them once set.
• Being able to copy the formatting from one column to the next

Incentivized

ClickHouse outperforms, especially in costs, since its compression/indexing engines are so smart, and even with very low computing power, you can already perform huge analyses of the data.

Incentivized

Grist is easier to use, faster, and loads quicker with heavy data.

• 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's saved a lot of time in both creating an advertising database and managing it week to week effectively. I had previously created in others that haven't worked, and this does, saving me a good 1 hour weekly, and 5 hours or more each time I had problems with the last ones
• Being able to stay on track with this has meant I'm following up at the right time (advertisers) and keeping a professional manner and not losing business due to missed communication
• Saving me $ from buying a program like Access (or Airtable monthly) and then the learning curve that that has. This has a much easier learning curve to say the least.

Incentivized