Gyxi is consumption based and very affordable.

The advantage of consumption based pricing is that you only pay for what you use.

However, a disadvantage of consumption based pricing is that it is difficult to predict exactly how much the cost will be.

20% of the alternatives

Saying Gyxi is affordable is justified, as the pricing is approximately 20% of alternatives such as Cosmos DB.

However, Cosmos DB calculates based on RU (Request Units), which is extremely difficult to calculate and predict. 

Gyxi calculates cost based on a flat fee for 1 million operations. That is every operation, whether listing 1000 items or adding a single item. It keeps things simple.

Cosmos DB consumes RU which is high for complex operations, such as queries or retrieving a big volume of data. One operation may cost hundreds of RU so pricing is not directly comparable.

One reason why Gyxi ends up being far more affordable is that it is only possible to perform simple operations in Gyxi. Most notably, there are no queries in Gyxi. Instead views are used to make sure data is already available in the way that it is needed.

Updating a view counts as an operation

When saving an item on a type that has 5 views, this will result in a consumption of 6 operations. One to save the item and 5 more to update the 5 views. 

Pricing example

Say you have a database with 10 GB of data.

You have an operation every second of the day during daytime and also at night time (for nightly batch jobs and such), then the total number of operations for that day will be 86,000.

For a full month, you have 2.5 million operations.

The first million is free and the remaining operations cost €1.1 per month. Plus €1 for the 10 GB data and your entire production database, with operations every second around the clock, costs you just over €2 per month.

That is how mind-bogglingly affordable Gyxi is.

So when you are considering whether to run that extra nightly job that would be nice to have but you are not sure you need … at least you don’t have to worry about the cost of your database.