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marcominerva/SqlDatabaseVectorSearch

A Blazor Web App and Minimal API for performing RAG (Retrieval Augmented Generation) and vector search using the native VECTOR type in Azure SQL Database and Azure OpenAI.

★144STARS
⑂38FORKS
!1ISSUES
🏆#14,485GLOBAL RANK
🔥9DAYS TRENDING
🚀
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Momentum

+10

STARS · LAST 30 DAYS

1

PER DAY

#839

MOST-STARRED C#

Window7 days30 days90 days
Stars gained+0+10+90
Per day111
Forks gained+0+3+10

SqlDatabaseVectorSearch gained 10 stars in the last 30 days, about 1 a day, and now has 144. It is about 2 years old and has averaged roughly 72 stars a year. It ranks #839 among C# repositories and #14,485 across all languages on GitHubRepo.

Trending Record

SqlDatabaseVectorSearch has maintained a continuous presence across global trending indexes, peaking at #11335. Below is the 30-day activity profile:

💡 Overview

SqlDatabaseVectorSearch is an open-source project written in C#: A Blazor Web App and Minimal API for performing RAG (Retrieval Augmented Generation) and vector search using the native VECTOR type in Azure SQL Database and Azure OpenAI.

Engineered for speed, consistency, and developer ease, it solves common hurdles in azure-openai, azure-sql-database, c-sharp. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.

⚡ Key Features

1

Optimized execution pipeline written in C# for predictable speed.

2

Zero-friction configuration with comprehensive sensible defaults out of the box.

3

Cross-platform runtime support across Linux, macOS, and Windows environments.

4

Strong typing and modular architecture designed for easy extension and maintainability.

5

Standardized CLI and API interfaces for smooth integration into CI/CD workflows.

6

Active community maintenance with regular dependency updates and security patches.

📥 Installation

terminal
$ git clone https://github.com/marcominerva/SqlDatabaseVectorSearch.git
cd SqlDatabaseVectorSearch

⚙ System Requirements

Platforms

  • • macOS
  • • Linux
  • • Windows

Runtime & Dependencies

C# environment and standard tooling

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

SqlDatabaseVectorSearch coordinates its core functionality through a modular C# pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.

🎯 Production Use Cases

Autonomous AI Agents

Orchestrate intelligent workflows and tool-calling routines with SqlDatabaseVectorSearch.

Model Inference & Prompting

Integrate fast, local or cloud-hosted generative AI models directly into production code.

Context Memory & RAG

Augment language models with dynamic vector retrieval and structured project memory.

Developer Productivity

Automate repetitive engineering tasks, code generation, and test creation using AI agents.

🚀 Getting Started

1

Install SqlDatabaseVectorSearch using your package manager: `git clone https://github.com/marcominerva/SqlDatabaseVectorSearch.git`

2

Initialize your project workspace or configuration file for SqlDatabaseVectorSearch.

3

Import SqlDatabaseVectorSearch into your codebase or invoke it directly from your terminal.

4

Execute your test suite or run `SqlDatabaseVectorSearch --help` to verify successful setup.

👍 Strengths

Active community backing with 144 GitHub stars and verified adoption.
Permissive open-source distribution under the MIT license.
Built in C# for high execution speed and developer familiarity.
Cross-platform compatibility across modern Linux, macOS, and Windows environments.
Clean modular design allowing flexible configuration and pipeline integration.

⚠️ Considerations

Requires familiarity with C# and modern CLI workflows.
Ecosystem extensions may require manual configuration depending on environment constraints.
Active development roadmap means breaking API changes may occur across major versions.

⇄ Alternatives & Direct Competitors

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👥 Who Should Use This

Developers and engineering teams building with C#, seeking reliable, tested, and actively maintained tooling for production workloads.

🏆 Nearby in the Rankings

marcominerva/SqlDatabaseVectorSearch is currently ranked #14,485 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

RankRepositoryLanguageStarsAction
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#14,429 samuelit0davila/fifa-street-pc-port C# ★ 145 Compare ↗
#14,485 marcominerva/SqlDatabaseVectorSearch This Project C# ★ 144
#14,485 azendal/elastic CSS ★ 144 Compare ↗
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Frequently Asked Questions

What does SqlDatabaseVectorSearch do? +

A Blazor Web App and Minimal API for performing RAG (Retrieval Augmented Generation) and vector search using the native VECTOR type in Azure SQL Database and Azure OpenAI.

What language is SqlDatabaseVectorSearch written in? +

The primary language is C#. Topics include: azure-openai, azure-sql-database, c-sharp, chatgpt, dotnet.

Is SqlDatabaseVectorSearch actively maintained? +

Yes, the last recorded push was on Oct 7, 2026 with 1 open issues being tracked.

How many stars does SqlDatabaseVectorSearch have? +

SqlDatabaseVectorSearch has 144 stars and 38 forks on GitHub.

How does SqlDatabaseVectorSearch rank among GitHub repositories? +

With 144 stars, marcominerva/SqlDatabaseVectorSearch is ranked #14,485 globally across all repositories tracked on GitHubRepo and #839 among C# projects.

What license is SqlDatabaseVectorSearch distributed under? +

The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.

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