Publications de Anastasia Ailamaki

The Effectiveness of Compression for GPU-Accelerated Queries on Out-of-Memory Datasets

Anastasia Ailamaki, Hamish Mcniece Hill Nicholson

ACM2025

Static Typing Meets Adaptive Optimization: A Unified Approach to Recursive Queries

Anastasia Ailamaki, Martin Odersky, Anna Patricia Herlihy

Writing correct and efficient recursive SQL queries is exceptionally challenging because recursive queries risk returning incorrect results, throwing runtime exceptions, or never terminating. Failures in recursive query execution fall into two categories: ...

ACM2025

Trustworthy and Efficient LLMs Meet Databases

Anastasia Ailamaki

In the rapidly evolving AI era with large language models (LLMs) at the core, making LLMs more trustworthy and efficient, especially in output generation (inference), has gained significant attention. This is to reduce plausible but faulty LLM outputs (a.k ...

2024

Adaptive Recursive Query Optimization

Anastasia Ailamaki, Martin Odersky, Guillaume André Fradji Martres, Anna Patricia Herlihy

Performance-critical industrial applications, including large-scale program, network, and distributed system analyses, are increasingly reliant on recursive queries for data analysis. Yet traditional relational algebra-based query optimization techniques d ...

IEEE2024

PixelsDB: Serverless and NL-Aided Data Analytics with Flexible Service Levels and Prices

Anastasia Ailamaki

Serverless query processing has become increasingly popular due to its advantages, including automated resource management, high elasticity, and pay-as-you-go pricing. For users who are not system experts, serverless query processing greatly reduces the co ...

2024

Oligolithic Cross-task Optimizations across Isolated Workloads

Anastasia Ailamaki, Eleni Zapridou, Panagiotis Sioulas

Enterprises collect data in large volumes and leverage them to drive numerous concurrent decisions and business processes. Their teams deploy multiple applications that often operate concurrently on the same data and infrastructure but have widely differen ...

2024

Efficient Model-Relational Data Management: Challenges and Opportunities

Anastasia Ailamaki, Viktor Sanca

2024

Efficient Data Access Paths for Mixed Vector-Relational Search

Anastasia Ailamaki, Viktor Sanca

2024

Optimizing Goodput through Sharing for Batch Analytics with Deadlines

Anastasia Ailamaki, Panagiotis Sioulas, Ioannis Mytilinis, Srinivas Karthik Venkatesh

Modern big data systems process not only a huge volume of data, but also numerous concurrent queries. These queries usually span over distributed data and need to be processed within a strict deadline (e.g.: report generation, SLA, etc.). While users expec ...

2024

Optimizing Context-Enhanced Relational Joins

Anastasia Ailamaki, Viktor Sanca

Collecting data, extracting value, and combining insights from relational and context-rich sources of many modalities in data processing pipelines presents a challenge for traditional relational DBMS. While relational operators enable declarative and optim ...

IEEE2024