We introduce Rosetta, a probabilistic range filter designed specifically for LSM-tree based
key-value stores. The core intuition is that we can sacrifice filter probe time because it is not …

Data series are a special type of multidimensional data present in numerous domains,
where similarity search is a key operation that has been extensively studied in the data …

Modern key-value stores typically rely on an LSM-tree in storage (SSD) to handle writes and
Bloom filters in memory (DRAM) to optimize reads. With ongoing advances in SSD …

Data-intensive key-value stores based on the Log-Structured Merge-Tree are used in
numerous modern applications ranging from social media and data science to cloud …

In the last 15 years, data series motif and discord discovery have emerged as two useful and
well-used primitives for data series mining, with applications to many domains, including …

Modern storage engines and key-value stores have come to rely on the log-structured
merge-tree (LSM-tree) as their core data structure. LSM-tree operates by gradually merge …

The analysis of time-series data associated with modernday industrial operations and
scientific experiments is now pushing both computational power and resources to their …

With the explosive growth of high-dimensional data, approximate methods emerge as
promising solutions for nearest neighbor search. Among alternatives, quantization methods …

Log-structured merge (LSM) trees have emerged as one of the most commonly used storage-
based data structures in modern data systems as they offer high throughput for writes and …

Log-structured merge (LSM) trees have emerged as one of the most commonly used disk-
based data structures in modern data systems. LSM-trees employ out-of-place ingestion to …