Entity Framework Core is great for performing crud operations, but did you know that you can go beyond basic relational queries with Entity Framework Core? Do you need to store and query non-structured data in JSON documents? Do you have hierarchical data that you wish to query with Entity Framework Core? Are you required to keep historical information about data that has been modified or maybe even deleted? If you answered Yes to any of the above questions, this is the talk you do not want to miss.
Microsoft MVP Giorgi Dalakishvili shows the EFCore.Visualizer extension he wrote. You can use it to view the query plan of your queries directly inside Visual Studio.
When using Entity Framework Core for data access, all database exceptions are wrapped in DbUpdateException. If you need to know whether the exception was caused by a unique constraint, the value being too long, or the value missing for a required column, you need to dig into the concrete DbException subclass instance and check the error number to determine the exact cause. In this episode, learn how EntityFramework.Exceptions handles all the database-specific details and allows you to use typed exceptions for Entity Framework Core when your query violates database constraints.
Semantic search or search based on the meaning analyzes the context and intent behind the query term to provide relevant results. Using Vector embeddings, the data structure behind semantic search, you can supercharge your search to include text, images, and other types of data. With vector databases you can store and index vector embeddings and provide similarity search over these embeddings.
Entity Framework Core is great for performing crud operations, but did you know that you can go beyond basic relational queries with Entity Framework Core? Do you need to store and query non-structured data in JSON documents? Do you have hierarchical data that you wish to query with Entity Framework Core? Are you required to keep historical information about data that has been modified or maybe even deleted? If you answered Yes to any of the above questions, this is the talk you do not want to miss.
Semantic search or search based on the meaning analyzes the context and intent behind the query term to provide relevant results. Using Vector embeddings, the data structure behind semantic search, you can supercharge your search to include text, images, and other types of data. With vector databases you can store and index vector embeddings and provide similarity search over these embeddings.
A Visual Studio debugger visualizer that helps you analyze and understand Entity Framework Core query plans directly inside Visual Studio. Get instant insights into how your LINQ queries are translated to SQL and how they perform. Supported Databases: SQL Server, PostgreSQL, SQLite, MySQL and Oracle.
Entity Framework Core is great for performing crud operations, but did you know that you can go beyond basic relational queries with Entity Framework Core? Do you need to store spatial data or find the nearest points of interest to a given location?