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 …

Popular LSM-tree based key-value stores suffer from suboptimal and unpredictable
performance due to write amplification and write stalls that cause application performance to …

In this paper, we show that key-value stores backed by an LSM-tree exhibit an intrinsic trade-
off between lookup cost, update cost, and main memory footprint, yet all existing designs …

RocksDB is an embedded, high-performance, persistent keyvalue storage engine
developed at Facebook. Much of our current focus in developing and configuring RocksDB …

In this paper, we show that all mainstream LSM-tree based key-value stores in the literature
and in industry are suboptimal with respect to how they trade off among the I/O costs of …

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 …

Key-Value (KV) stores support many crucial applications and services. They perform fast in-
memory processing, but are still often limited by I/O performance. The recent emergence of …

We present TRIAD, a new persistent key-value (KV) store based on Log-Structured Merge
(LSM) trees. TRIAD improves LSM KV throughput by reducing the write amplification arising …

Modern key-value stores often use write-optimized indexes and compact in-memory indexes
to speed up read and write performance. One popular write-optimized index is the Log …

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 …