Understand how the principle of "store together what is accessed together" is a game-changer for database performance and scalability.

Sharing Software / IT Vacancies Contact me on Telegram @ 01225484368 to share vacancies

Generate MongoDB CRUD code in Dart using @MongoDocument annotations - ideal for clean, scalable backend models.

Learn how the MongoDB Extension for Hibernate ORM provides Java developers with the freedom and flexibility to build modern applications that leverage the benefits of MongoDB’s document model.

Generate MongoDB CRUD code in Dart using @MongoDocument annotations - ideal for clean, scalable backend models.

A code generator for MongoDB-backed Dart models using @MongoDocument annotations - build type-safe, maintainable backend layers.

Contribute to MaoZeoDung/doraeulbase development by creating an account on GitHub.

What is MongoDB? So, what is MongoDB? MongoDB is classified as a document-oriented NoSQL...

A fast, lightweight Dart web framework for building scalable server-side apps and APIs with MongoDB, MySQL, SQLite, WebSockets,...

A company is looking for a MEAN Stack Developer. Key Responsibilities Design, develop, maintain, test, and document high-quality software so

Nhóm 1 - CSDL Nâng Cao - Bán hàng. Contribute to khangBio/csdl_nangcao development by creating an account on GitHub.

Nov 14, 2025 - Nexthire is hiring a remote Backend Engineer. 📍Location: India.

CVE-2025-63291: When processing API requests, the Alteryx server 2022.1.1.42654 and 2024.1 used MongoDB object IDs to uniquely identify the data being requested by the caller. The Alteryx server did not check whether the authenticated user had permission to access the specifie...

We made the switch from AWS-hosted MongoDB Atlas to a self-hosted solution on Hetzner, resulting in a 90% reduction in costs while maintaining performance and reliability.

Healthcare data are generated in many different formats, which makes it difficult to integrate and reuse across institutions and studies. Standardisation is required to enable consistent large-scale analysis. The OMOP-CDM, developed by the OHDSI community, provides one widely adopted standard. Our framework achieves schema-agnostic transformation by extending upon existing literature in using human-readable YAML specification to support both relational (Microsoft SQL Server (MSSQL)) and document-based (MongoDB) data sources. It also incorporates critical production readiness features: provenance-aware mapping and support for incremental updates. We validated the pipeline using 2.7 million patient records and 27 million encounters across six hospitals spanning two decades of records. The resulting OMOP-CDM dataset demonstrated an acceptable level of data quality with a 97% overall passing rate based on the OHDSI Data Quality Dashboard check. Our work provides a reusable blueprint for large-scale data harmonisation, directly supporting real-world medical data research.

Hey devs, I’m in a weird spot. Coding fluency: ~0.5/10 (I know print("hello"), loops, and that’s...

Introduction When we started developing SynTour, a tourism platform designed to...

Node.js & Database Management Projects for ₹600-1500 INR. My [login to view URL] app is already deployed and the REST of the codebase runs fine on my Linux VPS. The missi