You will get a MongoDB slow query diagnosed, fixed and benchmarked, not a bigger tier

Yuvaraj A.Status: Offline
Yuvaraj A. Yuvaraj A.
Rising Talent

Let a pro handle the details

Buy Other Databases services from Yuvaraj, priced and ready to go.
Yuvaraj A.Status: Offline
Yuvaraj A. Yuvaraj A.
Rising Talent

Let a pro handle the details

Buy Other Databases services from Yuvaraj, priced and ready to go.

Project details

Your listing or search endpoint takes seconds — sometimes minutes — and you suspect the tier. Usually it is the query shape.

I work from the query plan, not the hardware. No cluster credentials needed to identify the defect class — a reproduction at your data-to-cache ratio confirms the diagnosis locally. You get written findings, measurements against at least two strategies, and implementation code for the fix.

Three query patterns I fix regularly:

Aggregation pipelines that join before filtering — the server materialises every row before the predicate runs. Reversing the join collapses documents examined from millions to hundreds.

Offset pagination — $skip generates every prior page and discards it. Page 500 pays for pages 1 to 499 on every request. Keyset pagination stays flat at any depth.

Unanchored regex search — the server reads the entire collection before returning nothing. An anchored prefix against an ESR index turns a six-second COLLSCAN into a two-millisecond IXSCAN.

Live demo: mongo-demo.ai-agentic-enterprises.com — pick page 500 and time it yourself.
Database Type
MongoDB
What's included
Service Tiers Starter
$149
Standard
$650
Advanced
$1,800
Delivery Time 3 days 7 days 14 days
Number of Revisions
123
Source Code
-

Frequently asked questions

Yuvaraj A.Status: Offline

About Yuvaraj

Yuvaraj A.Status: Offline
Senior Solutions Architect | Java, AWS, React, Node.js | AI & LLM
Chennai, India - 9:12 am local time
25+ years building the systems large companies run on — payments, order management and real-time data platforms for Goldman Sachs, Prudential Wealth Management, UK Post Office, IKEA and H&M. I now bring that same engineering standard to smaller teams, hands-on and directly.

WHAT I BUILD

• Backend & APIs — Java, Spring Boot, GoLang, Node.js, Python
• Frontend — React, TypeScript
• Cloud & DevOps — AWS (Certified Solutions Architect), GCP, Docker, CI/CD, Ansible (Red Hat Certified)
• Data & streaming — Kafka, Druid, MongoDB, SingleStore, Redis, DynamoDB
• AI & automation — LLM integration, RAG, self-hosted models, agentic workflows, n8n, KNIME

RECENT HANDS-ON WORK

• Built a self-hosted real-time voice agent — speech-to-text, local LLM inference and speech synthesis on GPU, tuned for sub-second response.
• Built and deployed a production React application with payment-gateway integration and serverless API endpoints.
• Deployed n8n agentic automation on AWS and KNIME workflows across GCP, AWS and local environments.

BACKGROUND

Architect and delivery leader across financial services, retail, telecom and government. Onshore delivery at client sites in London, Manchester, Preston, Stockholm and Santiago. Certified in Oracle Generative AI, Databricks Generative AI and Oracle AI Vector Search; AWS Certified Solutions Architect. Currently pursuing a BS in Data Science at IIT Madras.

HOW I WORK

I stay hands-on. You deal with me directly — no account manager, no handoff to a junior. I scope work in writing before starting, and I will tell you when a simpler approach than the one you asked for will get you there faster.

I am new to Upwork. I am not new to this work — happy to do a paid trial task so you can judge the output rather than the profile.

Message me with what you're trying to build and I'll tell you honestly whether I'm the right fit.

Steps for completing your project

After purchasing the project, send requirements so Yuvaraj can start the project.

Delivery time starts when Yuvaraj receives requirements from you.

Yuvaraj works on your project following the steps below.

Revisions may occur after the delivery date.

Reproduce the query shape in isolation

I rebuild your query shape locally against a seeded dataset at your data-to-cache ratio, so the numbers come from a running system rather than from reading the pipeline.

Identify the defect class: join before filter, $skip, or missing index

From explain("executionStats"): how many documents the server examines for every document it returns. A listing endpoint returning 20 rows should examine about 20.

Review the work, release payment, and leave feedback to Yuvaraj.