MongoDB vs ScyllaDB: Architecture Comparison

benchANT provides a detailed comparison of the architectures of MongoDB and ScyllaDB, highlighting their differences in performance and scalability. While both NoSQL databases promise high availability and scalability, their approaches diverge significantly. MongoDB is known for its ease of use and offers a replica set cluster for high availability and a sharded cluster for horizontal scalability, which can add operational complexity. It uses a B+-Tree index and supports various indexing strategies, making it suitable for range-based queries. ScyllaDB, on the other hand, is designed for performance-critical workloads and utilizes a shard-per-core approach, ensuring efficient hardware utilization and consistent performance. It uses a multi-primary architecture with a decentralized structure, facilitating easy horizontal scaling without additional services. ScyllaDB's architecture allows for easier data repartitioning and load balancing, providing clear advantages in scalability over MongoDB. The report includes insights into their internal storage mechanisms, with MongoDB employing a Wired Tiger engine and ScyllaDB using a commit log and memtables, demonstrating how these differences impact their handling of workloads. Companies like Discord and Numberly have migrated from MongoDB to ScyllaDB to address performance issues, underscoring ScyllaDB's suitability for high-throughput and low-latency applications. Additionally, a separate benchmark report compares the performance, scalability, and costs of MongoDB Atlas and ScyllaDB Cloud, offering deeper insights into their capabilities.