Question 1

How does YesSql compare to MongoDB for .NET apps?

Accepted Answer

YesSql offers transactional guarantees and SQL backend integration, which MongoDB lacks, but it may have higher latency and requires SQL management. It's better for teams needing ACID compliance with document storage in .NET environments.

Question 2

Is YesSql really free unlike RavenDb?

Accepted Answer

Yes, YesSql is open-source and free for all uses, while RavenDb requires commercial licensing for most production scenarios. This makes YesSql a cost-effective choice, but RavenDb might offer more polished features out-of-the-box.

Question 3

How to set up YesSql with PostgreSQL?

Accepted Answer

Install the YesSql NuGet package, configure the PostgreSQL connection string in your .NET app, and define document and index classes. Refer to the wiki and sample apps for specific configuration steps and best practices.

Question 4

Does YesSql support ACID transactions?

Accepted Answer

Yes, YesSql fully supports ACID transactions by leveraging the transactional capabilities of the underlying relational database, ensuring data consistency for all operations, as emphasized in the README's key features.

Question 5

What are YesSql's main limitations?

Accepted Answer

YesSql has limitations in horizontal scaling, advanced NoSQL features like auto-sharding, and performance overhead from the SQL layer. It's best for applications where transactional integrity and SQL integration are critical.

Question 6

How to implement map/reduce in YesSql?

Accepted Answer

Implement map/reduce by defining index classes with Map and Reduce methods in your .NET code, similar to other document databases. Check the sample projects in the repository for concrete examples and testing patterns.

Question 7

Can YesSql handle large-scale datasets efficiently?

Accepted Answer

YesSql can handle large datasets, but performance depends on the underlying SQL database's tuning and scalability. It may not match the horizontal scaling ease of native NoSQL databases like MongoDB for massive data volumes.

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