Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM54453
Volume:
9 |
11 |
Nov 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Anyone who’s worked with Azure Cosmos DB knows the frustration. The platform has its own SQL dialect that doesn’t quite match what you’re used to. You need to constantly think about partitions when writing queries. And there’s no schema enforcement which sounds great until you realize how easy it is to accidentally break things. sure, we have tools like Prisma and Mongoose that make database work easier. They’re genuinely great at what they do. But here’s the problem: they were designed for completely different databases. Prisma targets relational databases, Mongoose was built for MongoDB. Neither one really gets what makes Cosmos DB different, so developers are left figuring things out on their own. We wanted to see if we could do better. This paper looks at four different ways to work with Cosmos DB: writing raw SQL queries, using Prisma-style interfaces, following Mongoose’s patterns, and using a new ODM we built specifically for Cosmos. Our version has Zod validation for catching schema issues, typed field references so you don’t misspell things, automatic parameterization to prevent injection attacks, and a visual Explorer that actually understands Cosmos DB’s structure. We got several developers together and had them complete the same tasks using each method. We measured everything how accurate they were, how long tasks took, how much mental energy they burned, and how many errors they made. The difference was pretty clear. With the Cosmos-specific ODM, developers made far fewer mistakes. No more typos in field names, no more schema mismatches, way fewer syntax errors. Tasks got done faster, and the queries people wrote were more reliable and predictable. What this really tells us is that one-size-fits-all tools don’t work for specialized platforms. Cosmos DB has its own personality, its own quirks. It needs tools that understand those quirks. When developers have the right tools for the job, everything gets easier they write cleaner code,
KEYWORDS
Publication Date
11/27/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
0
Total views since publication
PDF Downloads
2
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...