Hadoop++: Making a Yellow Elephant Run Like a Cheetah (Without It Even Noticing). - Jens Dittrich; Jorge-Arnulfo Quiané-Ruiz; Alekh Jindal; Yagiz Kargin; Vinay Setty; Jörg Schad (Proc. VLDB Endow., 2010)

Relax and Let the Database Do the Partitioning Online. - Alekh Jindal; Jens Dittrich (BIRTE, 2011)

Towards a One Size Fits All Database Architecture. - Jens Dittrich; Alekh Jindal (CIDR, 2011)

Trojan data layouts: right shoes for a running elephant. - Alekh Jindal; Jorge-Arnulfo Quiané-Ruiz; Jens Dittrich (SoCC, 2011)

Only Aggressive Elephants are Fast Elephants. - Jens Dittrich; Jorge-Arnulfo Quiané-Ruiz; Stefan Richter 007; Stefan Schuh; Alekh Jindal; Jörg Schad (Proc. VLDB Endow., 2012)

OctopusDB : flexible and scalable storage management for arbitrary database engines. - Alekh Jindal (2012)

WWHow! Freeing Data Storage from Cages. - Alekh Jindal; Jorge-Arnulfo Quiané-Ruiz; Jens Dittrich (CIDR, 2013)

How Achaeans Would Construct Columns in Troy. - Alekh Jindal; Felix Martin Schuhknecht; Jens Dittrich; Karen Khachatryan; Alexander Bunte (CIDR, 2013)

CARTILAGE: adding flexibility to the Hadoop skeleton. - Alekh Jindal; Jorge-Arnulfo Quiané-Ruiz; Samuel Madden 001 (SIGMOD Conference, 2013)

Performance and resource modeling in highly-concurrent OLTP workloads. - Barzan Mozafari; Carlo Curino; Alekh Jindal; Samuel Madden 001 (SIGMOD Conference, 2013)

A Comparison of Knives for Bread Slicing. - Alekh Jindal; Endre Palatinus; Vladimir Pavlov; Jens Dittrich (Proc. VLDB Endow., 2013)

The Uncracked Pieces in Database Cracking. - Felix Martin Schuhknecht; Alekh Jindal; Jens Dittrich (Proc. VLDB Endow., 2013)

GRAPHiQL: A graph intuitive query language for relational databases. - Alekh Jindal; Samuel Madden 001 (IEEE BigData, 2014)

VERTEXICA: Your Relational Friend for Graph Analytics! - Alekh Jindal; Praynaa Rawlani; Eugene Wu 002; Samuel Madden 001; Amol Deshpande; Mike Stonebraker (Proc. VLDB Endow., 2014)

Graph analytics using vertica relational database. - Alekh Jindal; Samuel Madden 001; Malú Castellanos; Meichun Hsu (IEEE BigData, 2015)

Robust Data Transformations. - Alekh Jindal (CIDR, 2015)

BigDansing: A System for Big Data Cleansing. - Zuhair Khayyat; Ihab F. Ilyas; Alekh Jindal; Samuel Madden 001; Mourad Ouzzani; Paolo Papotti; Jorge-Arnulfo Quiané-Ruiz; Nan Tang 001; Si Yin (SIGMOD Conference, 2015)

GraphFrames: an integrated API for mixing graph and relational queries. - Ankur Dave; Alekh Jindal; Li Erran Li; Reynold Xin; Joseph Gonzalez 001; Matei Zaharia (GRADES, 2016)

Amoeba: A Shape changing Storage System for Big Data. - Anil Shanbhag; Alekh Jindal; Yi Lu 010; Samuel Madden 001 (Proc. VLDB Endow., 2016)

An experimental evaluation and analysis of database cracking. - Felix Martin Schuhknecht; Alekh Jindal; Jens Dittrich (VLDB J., 2016)

A robust partitioning scheme for ad-hoc query workloads. - Anil Shanbhag; Alekh Jindal; Samuel Madden 001; Jorge-Arnulfo Quiané-Ruiz; Aaron J. Elmore (SoCC, 2017)

INGESTBASE: A Declarative Data Ingestion System. - Alekh Jindal; Jorge-Arnulfo Quiané-Ruiz; Samuel Madden 001 (CoRR, 2017)

AdaptDB: Adaptive Partitioning for Distributed Joins. - Yi Lu 010; Anil Shanbhag; Alekh Jindal; Samuel Madden 001 (Proc. VLDB Endow., 2017)

Query and Resource Optimization: Bridging the Gap. - Lalitha Viswanathan; Alekh Jindal; Konstantinos Karanasos (ICDE, 2018)

Computation Reuse in Analytics Job Service at Microsoft. - Alekh Jindal; Shi Qiao 001; Hiren Patel; Zhicheng Yin; Jieming Di; Malay Bag; Marc T. Friedman; Yifung Lin; Konstantinos Karanasos; Sriram Rao (SIGMOD Conference, 2018)

Selecting Subexpressions to Materialize at Datacenter Scale. - Alekh Jindal; Konstantinos Karanasos; Sriram Rao; Hiren Patel (Proc. VLDB Endow., 2018)

Towards a Learning Optimizer for Shared Clouds. - Chenggang Wu 001; Alekh Jindal; Saeed Amizadeh; Hiren Patel; Wangchao Le; Shi Qiao 001; Sriram Rao (Proc. VLDB Endow., 2018)

Peregrine: Workload Optimization for Cloud Query Engines. - Alekh Jindal; Hiren Patel; Abhishek Roy 008; Shi Qiao 001; Zhicheng Yin; Rathijit Sen; Subru Krishnan (SoCC, 2019)

Big Data Processing at Microsoft: Hyper Scale, Massive Complexity, and Minimal Cost. - Hiren Patel; Alekh Jindal; Clemens A. Szyperski (SoCC, 2019)

Query and Resource Optimizations: A Case for Breaking the Wall in Big Data Systems. - Alekh Jindal; Lalitha Viswanathan; Konstantinos Karanasos (CoRR, 2019)

SparkCruise: Handsfree Computation Reuse in Spark. - Abhishek Roy 008; Alekh Jindal; Hiren Patel; Ashit Gosalia; Subru Krishnan; Carlo Curino (Proc. VLDB Endow., 2019)

Robust Data Partitioning. - Alekh Jindal; Anil Shanbhag; Yi Lu 010 (Encyclopedia of Big Data Technologies, 2019)

Cloudy with high chance of DBMS: a 10-year prediction for Enterprise-Grade ML. - Ashvin Agrawal; Rony Chatterjee; Carlo Curino; Avrilia Floratou; Neha Godwal; Matteo Interlandi; Alekh Jindal; Konstantinos Karanasos; Subru Krishnan; Brian Kroth; Jyoti Leeka; Kwanghyun Park 001; et al. (CIDR, 2020)

Towards Plan-aware Resource Allocation in Serverless Query Processing. - Malay Bag; Alekh Jindal; Hiren Patel (HotCloud, 2020)

Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings. - Tarique Siddiqui; Alekh Jindal; Shi Qiao 001; Hiren Patel; Wangchao Le (SIGMOD Conference, 2020)

Seagull: An Infrastructure for Load Prediction and Optimized Resource Allocation. - Olga Poppe; Tayo Amuneke; Dalitso Banda; Aritra De; Ari Green; Manon Knoertzer; Ehi Nosakhare; Karthik Rajendran; Deepak Shankargouda; Meina Wang; Alan Au; Carlo Curino; et al. (Proc. VLDB Endow., 2020)

AutoToken: Predicting Peak Parallelism for Big Data Analytics at Microsoft. - Rathijit Sen; Alekh Jindal; Hiren Patel; Shi Qiao 001 (Proc. VLDB Endow., 2020)

Applied Research Lessons from CloudViews Project. - Alekh Jindal (SIGMOD Rec., 2020)

Magpie: Python at Speed and Scale using Cloud Backends. - Alekh Jindal; K. Venkatesh Emani; Maureen Daum; Olga Poppe; Brandon Haynes; Anna Pavlenko; Ayushi Gupta; Karthik Ramachandra 002; Carlo Curino; Andreas Müller 024; Wentao Wu 001; Hiren Patel (CIDR, 2021)

Production Experiences from Computation Reuse at Microsoft. - Alekh Jindal; Shi Qiao 001; Hiren Patel; Abhishek Roy 008; Jyoti Leeka; Brandon Haynes (EDBT, 2021)

Microlearner: A fine-grained Learning Optimizer for Big Data Workloads at Microsoft. - Alekh Jindal; Shi Qiao 001; Rathijit Sen; Hiren Patel (ICDE, 2021)

Steering Query Optimizers: A Practical Take on Big Data Workloads. - Parimarjan Negi; Matteo Interlandi; Ryan Marcus; Mohammad Alizadeh; Tim Kraska; Marc T. Friedman; Alekh Jindal (SIGMOD Conference, 2021)

Optimal Resource Allocation for Serverless Queries. - Anish Pimpley; Shuo Li; Anubha Srivastava; Vishal Rohra; Yi Zhu; Soundararajan Srinivasan; Alekh Jindal; Hiren Patel; Shi Qiao 001; Rathijit Sen (CoRR, 2021)

PerfGuard: Deploying ML-for-Systems without Performance Regressions, Almost! - H. M. Sajjad Hossain; Marc T. Friedman; Hiren Patel; Shi Qiao 001; Soundar Srinivasan; Markus Weimer; Remmelt Ammerlaan; Lucas Rosenblatt; Gilbert Antonius; Peter Orenberg; Vijay Ramani; Abhishek Roy 008; et al. (Proc. VLDB Endow., 2021)

Machine Learning for Cloud Data Systems: the Promise, the Progress, and the Path Forward. - Alekh Jindal; Matteo Interlandi (Proc. VLDB Endow., 2021)

The Cosmos Big Data Platform at Microsoft: Over a Decade of Progress and a Decade to Look Forward. - Conor Power; Hiren Patel; Alekh Jindal; Jyoti Leeka; Bob Jenkins; Michael Rys; Ed Triou; Dexin Zhu; Lucky Katahanas; Chakrapani Bhat Talapady; Josh Rowe; Fan Zhang; et al. (Proc. VLDB Endow., 2021)

SparkCruise: Workload Optimization in Managed Spark Clusters at Microsoft. - Abhishek Roy 008; Alekh Jindal; Priyanka Gomatam; Xiating Ouyang; Ashit Gosalia; Nishkam Ravi; Swinky Mann; Prakhar Jain (Proc. VLDB Endow., 2021)

AutoExecutor: Predictive Parallelism for Spark SQL Queries. - Rathijit Sen; Abhishek Roy 008; Alekh Jindal; Rui Fang; Jeff Zheng; Xiaolei Liu; Ruiping Li (Proc. VLDB Endow., 2021)

Phoebe: A Learning-based Checkpoint Optimizer. - Yiwen Zhu; Matteo Interlandi; Abhishek Roy 008; Krishnadhan Das; Hiren Patel; Malay Bag; Hitesh Sharma; Alekh Jindal (Proc. VLDB Endow., 2021)

Towards Optimal Resource Allocation for Big Data Analytics. - Anish Pimpley; Shuo Li; Rathijit Sen; Soundararajan Srinivasan; Alekh Jindal (EDBT, 2022)

Deploying a Steered Query Optimizer in Production at Microsoft. - Wangda Zhang; Matteo Interlandi; Paul Mineiro; Shi Qiao 001; Nasim Ghazanfari; Karlen Lie; Marc T. Friedman; Rafah Hosn; Hiren Patel; Alekh Jindal (SIGMOD Conference, 2022)

Pipemizer: An Optimizer for Analytics Data Pipelines. - Sunny Gakhar; Joyce Cahoon; Wangchao Le; Xiangnan Li; Kaushik Ravichandran 002; Hiren Patel; Marc T. Friedman; Brandon Haynes; Shi Qiao 001; Alekh Jindal; Jyoti Leeka (Proc. VLDB Endow., 2022)

Diversity and Inclusion Activities in Database Conferences: A 2021 Report. - Sihem Amer-Yahia; Yael Amsterdamer; Sourav S. Bhowmick; Angela Bonifati; Philippe Bonnet; Renata Borovica-Gajic; Barbara Catania; Tania Cerquitelli; Silvia Chiusano; Panos K. Chrysanthis; Carlo Curino; Jérôme Darmont; et al. (SIGMOD Rec., 2022)

Query Optimizer as a Service: An Idea Whose Time Has Come! - Alekh Jindal; Jyoti Leeka (SIGMOD Rec., 2022)

Predictive Price-Performance Optimization for Serverless Query Processing. - Rathijit Sen; Abhishek Roy 008; Alekh Jindal (EDBT, 2023)

Making Data Clouds Smarter at Keebo: Automated Warehouse Optimization using Data Learning. - Barzan Mozafari; Radu Alexandru Burcuta; Alan Cabrera; Andrei Constantin; Derek Francis; David Grömling; Alekh Jindal; Maciej Konkolowicz; Valentin Marian Spac; Yongjoo Park; Russell Razo Carranzo; Nicholas Richardson; et al. (SIGMOD Conference Companion, 2023)

PikePlace: Generating Intelligence for Marketplace Datasets. - Shi Qiao 001; Alekh Jindal (Proc. VLDB Endow., 2023)

Front Matter. - Georgia Koutrika; Jun Yang 001; Manos Athanassoulis; Kostas Stefanidis; Ju Fan; Abdul Quamar; Yuanyan Tian; Alekh Jindal; Carsten Binnig; Jennie Rogers; Senjuti Basu Roy; Steven Euijong Whang; et al. (Proc. VLDB Endow., 2023)

Diversity, Equity and Inclusion Activities in Database Conferences: A 2022 Report. - Sihem Amer-Yahia; Divyakant Agrawal; Yael Amsterdamer; Sourav S. Bhowmick; Angela Bonifati; Renata Borovica-Gajic; Jesús Camacho-Rodríguez; Barbara Catania; Panos K. Chrysanthis; Carlo Curino; Jérôme Darmont; Gillian Dobbie; et al. (SIGMOD Rec., 2023)

GEqO: ML-Accelerated Semantic Equivalence Detection. - Brandon Haynes; Rana Alotaibi; Anna Pavlenko; Jyoti Leeka; Alekh Jindal; Yuanyuan Tian 001 (Proc. ACM Manag. Data, 2023)

Turning Databases Into Generative AI Machines. - Alekh Jindal; Shi Qiao 001; Sathwik Madhula; Kanupriya Raheja; Sandhya Jain (CIDR, 2024)

Sibyl: Forecasting Time-Evolving Query Workloads. - Hanxian Huang; Tarique Siddiqui; Rana Alotaibi; Carlo Curino; Jyoti Leeka; Alekh Jindal; Jishen Zhao; Jesús Camacho-Rodríguez; Yuanyuan Tian 001 (Proc. ACM Manag. Data, 2024)

Searching Clinical Data Using Generative AI. - Karan Hanswadkar; Anika Kanchi; Shivani Tripathi; Shi Qiao 001; Rony Chatterjee; Alekh Jindal (CoRR, 2025)

Prompt Migration: Stabilizing GenAI Applications with Evolving Large Language Models. - Shivani Tripathi; Pushpanjali Nema; Aditya Halder; Shi Qiao 001; Alekh Jindal (CoRR, 2025)