Comparative Analysis of RocksDB, LMDB, and MongoDB: A Performance Evaluation

Abstract

<div class="section abstract"><div class="htmlview paragraph">This abstract provides a comprehensive comparison between RocksDB, LMDB, and MongoDB, three popular database systems, highlighting their differences in terms of architecture, performance, scalability, and use cases.</div><div class="htmlview paragraph">RocksDB, an embedded key-value store developed by Facebook, and LMDB (Lightning Memory-Mapped Database), a memory-mapped key-value store, are both optimized for high-performance and low-latency workloads. These databases excel in scenarios where efficiency and speed are critical factors, such as caching, session stores, and other applications that require fast data access. RocksDB is known for its persistent storage on disk and seamless integration with various programming languages, while LMDB leverages memory-mapped files for exceptional performance but lacks distributed capabilities. On the other hand, MongoDB, a document-oriented NoSQL database, offers a flexible schema and a rich set of features for handling complex data structures. MongoDB is highly scalable and suitable for applications requiring dynamic and evolving data models. It provides robust support for sharding and replication, allowing horizontal scaling across multiple nodes, making it ideal for large-scale distributed environments and cloud-native applications. In terms of data consistency, RocksDB and LMDB prioritize strong consistency, ensuring data integrity even in the face of failures. In contrast, MongoDB offers eventual consistency by default, providing improved scalability but potentially sacrificing immediate data consistency.Each database system has its strengths and weaknesses, and choosing the appropriate one depends on specific application requirements. RocksDB and LMDB are preferred for their superior performance and low latency, while MongoDB excels in scalability, flexibility, and handling complex data structures.</div></div>