# LSM-based Storage Techniques: A Survey

## TL;DR

This survey reviews recent advancements in Log-Structured Merge-tree (LSM-tree) storage techniques, classifying research efforts, analyzing their strengths and trade-offs, and discussing future directions in NoSQL systems.

## Contribution

It provides a comprehensive taxonomy and detailed survey of recent LSM-tree research, highlighting key improvements and open challenges.

## Key findings

- Classified LSM-tree research into a clear taxonomy
- Analyzed strengths and trade-offs of various LSM-based systems
- Identified promising future research directions

## Abstract

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 of research efforts, from both the database community and the operating systems community, that try to improve various aspects of LSM-trees. In this paper, we provide a survey of recent research efforts on LSM-trees so that readers can learn the state-of-the-art in LSM-based storage techniques. We provide a general taxonomy to classify the literature of LSM-trees, survey the efforts in detail, and discuss their strengths and trade-offs. We further survey several representative LSM-based open-source NoSQL systems and discuss some potential future research directions resulting from the survey.