We present the first learned index that supports predecessor, range queries and updates
within provably efficient time and space bounds in the worst case. In the (static) context of …

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 …

Alibaba runs the largest e-commerce platform in the world serving more than 600 million
customers, with a GMV (gross merchandise value) exceeding USD 768 billion in FY2018 …

Log-structured merge (LSM) trees offer efficient ingestion by appending incoming data, and
thus, are widely used as the storage layer of production NoSQL data stores. To enable …

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 …

Data-intensive applications fueled the evolution of log structured merge (LSM) based key-
value engines that employ the out-of-place paradigm to support high ingestion rates with low …

Particle filters avoid parametric estimates for Bayesian posterior densities, which alleviates
Gaussian assumptions in nonlinear regimes. These methods, however, are more sensitive …

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 …