Build smarter .NET applications by transforming complex data and delivering relevant search experiences with MongoDB aggregation, Search, and Vector Search.
Key Features:
- Transform complex data with MongoDB aggregation pipelines
- Build relevant search functionality in .NET with MongoDB Search
- Add semantic search to C# applications with MongoDB Vector Search
- Purchase of the print or Kindle book includes a free PDF eBook
Book Description:
Modern .NET applications often need more than basic data retrieval: they need to reshape complex data and help users find the right information. Building Modern Data Applications with MongoDB and .NET shows you how to solve these problems with MongoDB aggregation and search features in C#.
You'll start by building aggregation pipelines and integrating them into an application. Next, you'll create more relevant search functionality with MongoDB Search before moving to semantic search with MongoDB Vector Search.
Along the way, you'll learn best practices for each area, helping you make sound design choices as application requirements grow. Written by Luce Carter, Senior Developer Advocate at MongoDB and Microsoft MVP for Developer Technologies, the book combines deep product knowledge with a developer-focused approach to help you move confidently from advanced querying to search and vector search in .NET.
What You Will Learn:
- Build aggregation pipelines to reshape complex application data
- Integrate aggregation pipelines into C#/.NET applications
- Improve search relevance with MongoDB Search
- Add full-text search to .NET applications
- Implement semantic search with MongoDB Vector Search
- Integrate vector search into C# applications
- Apply best practices to aggregation and search
Who this book is for:
This book is for C#/.NET developers and backend engineers who use MongoDB and want to move beyond basic queries. It suits readers who need to transform complex data, improve application search, or add semantic search. A working knowledge of C#/.NET and basic familiarity with MongoDB is recommended.
Table of Contents
- Transform your data with the aggregation framework
- Add aggregations to the application
- Performance Optimization for Aggregations
- Search your data with MongoDB Search
- Adding MongoDB Search to the application
- Best practices for MongoDB Search
- Search your data semantically with MongoDB Vector Search
- Adding MongoDB Vector Search to the application
- Best practices for MongoDB Vector Search
- Key takeaways and Next Steps