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Aditya Badramraju

Speaker

Aditya Badramraju

3

talks

Product Manager Microsoft

Aditya Badramraju is a Program Manager for Azure SQL at Microsoft, driving innovation in performance, scalability, and resiliency. He leads strategic initiatives to accelerate mission-critical workloads, enhance concurrency and throughput, and deliver capabilities for customers modernizing their data platforms on Azure. He collaborates with engineering teams, field experts, and enterprise customers to evaluate real-world performance scenarios and database architectures, informing product strategy and roadmap decisions. His expertise includes database internals, observability, and cost-performance optimization.

Bio from: Microsoft Ignite 2025

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Talks & appearances

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Meet the performance-enhanced next gen Azure SQL Managed Instance

Meet the performance-enhanced next gen Azure SQL Managed Instance

2025-11-19 · Microsoft Ignite 2025 Watch
breakout
with Aditya Badramraju (Microsoft) , Craig Henninger (Hexure) , Troy Brovold (Hexure) , Anitha Adusumilli (Microsoft)
AI/ML Azure SQL

Get 2X performance and 5X database capacity with Azure SQL Managed Instance. The new next-gen General Purpose tier sets a new standard of value for fully managed SQL solutions. Get started quickly with AI-assisted tooling that can complete an end-to-end migration in days. See this come to life with insurance services organization, Hexure who rebuilt their platform with Azure SQL Managed Instance and Azure App Service and delivered a better CX in one highly performant, scalable and efficient platform.

Build scalable AI apps with Azure SQL Database Hyperscale

Build scalable AI apps with Azure SQL Database Hyperscale

2025-11-19 · Microsoft Ignite 2025 Watch
breakout
with Ravi Mantena , Anna Hoffman (Azure Data) , Ross Jenkins (Hexagon ALI / Octave) , Aditya Badramraju (Microsoft) , Britt Ewen (BlackRock) , Dmitry Borodin (Hexagon Asset Lifecycle Intelligence)
AI/ML Azure Microsoft RAG SQL

Build AI apps that run securely and scale with your needs with Azure SQL Database Hyperscale. We’ll cover native vector indexes for semantic search, read scale out for low latency RAG, and secure model invocation with Microsoft Foundry, using the model of your choice, from T SQL. Hear directly from global technology company Hexagon and investment firm BlackRock who will join us to share their experience along with best practices, demos and more!

Get superior price and performance with Azure cloud-scale databases | BRK224H

Get superior price and performance with Azure cloud-scale databases | BRK224H

2023-11-17 · Microsoft Ignite 2023 Watch
video
with Bob Ward (Azure Data) , Denzil Ribeiro (Microsoft) , Ed Donahue , Vlad Rabenok , Maximilian Conrad , Chandra Gavaravarapu , Shireesh Thota (Microsoft) , Aditya Badramraju (Microsoft) , Xiaoxuan Guo , Parikshit Savjani , Simon Faber
AI/ML Azure Cloud Computing HTML Microsoft MySQL

Improve performance with the latest capabilities for Azure SQL Databases, Azure Database for PostgreSQL, and SQL Server enabled by Azure Arc for hybrid and multi-cloud. You’ll learn how customers enabled ongoing innovation by migrating to Azure Database for MySQL. This session will cover tactical ways to get the most from your applications with the databases that are easy to use, deliver unmatched price/performance, support open-source and enable transformative AI technologies.

To learn more, please check out these resources: * https://aka.ms/Ignite23CollectionsBRK224H * https://info.microsoft.com/ww-landing-contact-me-for-events-m365-in-person-events.html?LCID=en-us&ls=407628-contactme-formfill * https://aka.ms/ArcSQL * https://aka.ms/azure-ignite2023-dataaiblog

𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * Chandra Gavaravarapu * Maximilian Conrad * Shireesh Thota * Simon Faber * Vlad Rabenok * Xiaoxuan Guo * Ed Donahue * Aditya Badramraju * Bob Ward * Denzil Ribeiro * Parikshit Savjani

𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This video is one of many sessions delivered for the Microsoft Ignite 2023 event. View sessions on-demand and learn more about Microsoft Ignite at https://ignite.microsoft.com

BRK224H | English (US) | Data

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