Software Alternatives, Accelerators & Startups

Microsoft SQL VS Qdrant

Compare Microsoft SQL VS Qdrant and see what are their differences

Microsoft SQL logo Microsoft SQL

Microsoft SQL is a best in class relational database management software that facilitates the database server to provide you a primary function to store and retrieve data.

Qdrant logo Qdrant

Qdrant is a high-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
  • Microsoft SQL Landing page
    Landing page //
    2023-01-26
  • Qdrant Landing page
    Landing page //
    2023-12-20

Qdrant is a leading open-source high-performance Vector Database written in Rust with extended metadata filtering support and advanced features. It deploys as an API service providing a search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications. Powering vector similarity search solutions of any scale due to a flexible architecture and low-level optimization. Qdrant is trusted and high-rated by Machine Learning and Data Science teams of top-tier companies worldwide.

Microsoft SQL

Pricing URL
-
$ Details
-
Platforms
-
Release Date
-

Qdrant

$ Details
freemium
Platforms
Linux Windows Kubernetes Docker
Release Date
2021 May

Microsoft SQL features and specs

  • Comprehensive Feature Set
    SQL Server offers a wide range of features including advanced analytics, in-memory capabilities, robust security measures, and integration services.
  • High Performance
    With in-memory OLTP and support for persistent memory technologies, SQL Server provides high transaction and query performance.
  • Scalability
    SQL Server can scale from small installations on single machines to large, data-intensive applications requiring high throughput and storage.
  • Security
    SQL Server offers advanced security features like encryption, dynamic data masking, and advanced threat protection, ensuring data safety and compliance.
  • Integrations
    It easily integrates with other Microsoft products such as Azure, Power BI, and Active Directory, providing a cohesive ecosystem for enterprise solutions.
  • Developer Friendly
    It supports a wide range of development tools and languages including .NET, Python, Java, and more, making it highly versatile for developers.
  • High Availability
    Features like Always On availability groups and failover clustering provide high availability and disaster recovery options for critical applications.

Possible disadvantages of Microsoft SQL

  • Cost
    SQL Server can be expensive, particularly for the Enterprise edition. Licensing costs can add up quickly depending on the features and scale required.
  • Complexity
    Due to its comprehensive feature set, SQL Server can be complex to configure and manage, requiring skilled administrators and developers.
  • Resource Intensive
    SQL Server can be resource-intensive, requiring substantial hardware resources for optimal performance, which can increase overall operational costs.
  • Windows-Centric
    While SQL Server can run on Linux, it is primarily optimized for and tightly integrated with the Windows ecosystem, which may not suit all organizations.
  • Vendor Lock-In
    Being a proprietary solution, it can cause vendor lock-in, making it challenging to switch to alternative database systems without significant migration efforts.

Qdrant features and specs

  • Advanced Filtering
  • On-disc Storage
  • Scalar Quantization
  • Product Quantization
  • Binary Quantization
  • Sparse Vectors
  • Hybrid Search
  • Discovery API
  • Recommendation API

Microsoft SQL videos

3.1 Microsoft SQL Server Review

More videos:

  • Review - What is Microsoft SQL Server?
  • Review - Querying Microsoft SQL Server (T-SQL) | Udemy Instructor, Phillip Burton [bestseller]

Qdrant videos

No Qdrant videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Microsoft SQL and Qdrant)
Databases
79 79%
21% 21
Relational Databases
100 100%
0% 0
Search Engine
0 0%
100% 100
Tool
100 100%
0% 0

Questions and Answers

As answered by people managing Microsoft SQL and Qdrant.

Why should a person choose your product over its competitors?

Qdrant's answer:

Advanced Features, Performance, Scalability, Developer Experience, and Resources Saving.

What makes your product unique?

Qdrant's answer:

Highest performance https://qdrant.tech/benchmarks/, scalability and ease of use.

Which are the primary technologies used for building your product?

Qdrant's answer:

Qdrant is written completely in Rust. SDKs available for all popular languages Python, Go, Rust, Java, .NET, etc.

User comments

Share your experience with using Microsoft SQL and Qdrant. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, Qdrant seems to be more popular. It has been mentiond 57 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Microsoft SQL mentions (0)

We have not tracked any mentions of Microsoft SQL yet. Tracking of Microsoft SQL recommendations started around Mar 2021.

Qdrant mentions (57)

  • 10 open-source MCPs that make your AI agents smarter than your team lead
    Qdrant — open-source and super developer-friendly. - Source: dev.to / 3 days ago
  • Build Code-RAGent, an agent for your codebase
    The only thing left to do then was to build something that could showcase the power of code ingestion within a vector database, and it immediately clicked in my mind: "Why don't I ingest my entire codebase of solved Go exercises from Exercism?" That's how I created Code-RAGent, your friendly coding assistant based on your personal codebases and grounded in web search. It is built on top of GPT-4.1, powered by... - Source: dev.to / 12 days ago
  • Ingest (almost) any non-PDF document in a vector database, effortlessly
    Qdrant is an easy-to-set-up, highly performing and scalable vector database, that offers numerous functionalities (among which hybrid search and metadata filtering). - Source: dev.to / 16 days ago
  • Why You Shouldn’t Invest In Vector Databases?
    In cases where a company possesses a strong technological foundation and faces a substantial workload demanding advanced vector search capabilities, its ideal solution lies in adopting a specialized vector database. Prominent options in this domain include Chroma (having raised $20 million), Zilliz (having raised $113 million), Pinecone (having raised $138 million), Qdrant (having raised $9.8 million), Weaviate... - Source: dev.to / 18 days ago
  • Preview 2 of .NET AI Chat Web App Template Now Available
    /filters:no_upscale()/news/2025/04/microsoft-dotnet-ai-template-p2/en/resources/1use-aspire-orchestration-1745167526397.png) A notable addition in Preview 2 is the support for .NET Aspire, enhancing the development toolkit with advanced AI capabilities. The Qdrant vector database can be utilized alongside .NET Aspire to create scalable applications. The template continues to utilize the Retrieval Augmented... - Source: dev.to / 20 days ago
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What are some alternatives?

When comparing Microsoft SQL and Qdrant, you can also consider the following products

MySQL - The world's most popular open source database

Milvus - Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

Vespa.ai - Store, search, rank and organize big data

SQLite - SQLite Home Page

Weaviate - Welcome to Weaviate