Predicting personalized sequential behavior is a key task for recommender systems. In order
to predict user actions such as the next product to purchase, movie to watch, or place to visit …

There are two types of high-performance graph processing engines: low-and high-level
engines. Low-level engines (Galois, PowerGraph, Snap) provide optimized data structures …

In many important applications—such as search engines and relational database systems—
data are stored in the form of arrays of integers. Encoding and, most importantly, decoding of …

Software systems that learn from user data with machine learning (ML) have become
ubiquitous over the last years. Recent law such as the" General Data Protection …

Analytical databases are continuously adapting to the underlying hardware in order to
saturate all sources of parallelism. At the same time, hardware evolves in multiple directions …

Many organizations are shifting to a data management paradigm called the" Lakehouse,"
which implements the functionality of structured data warehouses on top of unstructured …

In-memory tree structured index search is a fundamental database operation. Modern
processors provide tremendous computing power by integrating multiple cores, each with …

Join is an important database operation. As computer architectures evolve, the best join
algorithm may change hand. This paper re-examines two popular join algorithms--hash join …

This work aims at reducing the main-memory footprint in high performance hybrid OLTP &
OLAP databases, while retaining high query performance and transactional throughput. For …

In the past decades, advances in speed of commodity CPUs have far outpaced advances in
RAM latency. Main-memory access has therefore become a performance bottleneck for …