Recently, the log-structured merge-tree (LSM-tree) has been widely adopted for use in the
storage layer of modern NoSQL systems. Because of this, there have been a large number …

LSM-based KV stores are designed to offer good write performance, by capturing client
writes in memory, and only later flushing them to storage. Writes are later compacted into a …

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 …

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 …

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 cloud infrastructure motivates disaggregation of monolithic data stores into components
that are assembled together based on an application's workload. This study investigates …

Key-value stores (KV) have become one of the main components of the modern storage and
data processing system stack. With the increasing need for timely data analysis …

The recent byte-addressable and large-capacity commercialized persistent memory (PM) is
promising to drive database as a service (DBaaS) into unchartered territories. This paper …

In this article, we show that key-value stores backed by a log-structured merge-tree (LSM-
tree) exhibit an intrinsic tradeoff between lookup cost, update cost, and main memory …