About
A practical database recommendation resource for developers, architects, and teams choosing modern data systems.
Choosing the right database is not about picking the most popular option—it is about matching your database to your workload. The right choice depends on factors like workload type (OLTP vs OLAP), query complexity, schema evolution, latency requirements, and operational constraints.
Instead of relying on generic comparisons, modern systems require evaluating trade-offs across scalability, consistency, and performance.
WhatDbShouldIUse is a guided database selection tool that helps developers and teams compare SQL, NoSQL, vector databases, streaming systems, and analytical warehouses.
It narrows down database choices based on real-world constraints and provides a practical shortlist tailored to your use case.
This tool is designed for developers, backend engineers, architects, startups, and AI teams building modern applications.
Whether you are choosing a database for an MVP, scaling a production system, or designing AI-powered applications, the goal is to simplify decision-making.
The tool covers relational databases, NoSQL systems, vector databases for semantic search, streaming platforms, time-series databases, and analytical warehouses.
It supports modern use cases including real-time systems, AI retrieval (RAG), analytics, and large-scale distributed applications.
The guided picker evaluates your requirements across workload shape, consistency guarantees, query patterns, scaling strategy, and operational overhead.
Choosing the wrong database can lead to scaling issues, performance bottlenecks, and costly migrations. A structured approach helps avoid these problems early.
This tool focuses on real-world trade-offs instead of generic feature lists.
WhatDbShouldIUse is built to help teams make better database decisions using practical constraints instead of assumptions.
WhatDbShouldIUse is created by Akshith Varma Chittiveli, an engineer focused on building scalable systems and simplifying complex architecture decisions.
For updates and insights, connect on LinkedIn.
Use the guided tool to find the best database for your use case or explore common questions.