OceanBase Bacchus: a High-Performance and Scalable Cloud-Native Shared Storage Architecture for Multi-Cloud

TL;DR

OceanBase Bacchus introduces a scalable, high-performance shared storage architecture optimized for multi-cloud environments, significantly reducing storage costs while maintaining competitive read/write performance for both OLTP and OLAP workloads.

Contribution

The paper presents a novel LSM-tree based architecture with shared service-oriented logging and elastic scaling, addressing limitations of existing shared-storage systems in cloud-native databases.

Findings

Achieves performance comparable or superior to HBase and StarRocks in benchmarks.

Reduces storage costs by up to 89% in OLAP scenarios.

Supports multi-cloud deployment with high availability.

Abstract

Although an increasing number of databases now embrace shared-storage architectures, current storage-disaggregated systems have yet to strike an optimal balance between cost and performance. In high-concurrency read/write scenarios, B+-tree-based shared storage struggles to efficiently absorb frequent in-place updates. Existing LSM-tree-backed disaggregated storage designs are hindered by the intricate implementation of cross-node shared-log mechanisms, where no satisfactory solution yet exists. This paper presents OceanBase Bacchus, an LSM-tree architecture tailored for object storage provided by cloud vendors. The system sustains high-performance reads and writes while rendering compute nodes stateless through shared service-oriented PALF (Paxos-backed Append-only Log File system) logging and asynchronous background services. We employ a Shared Block Cache Service to flexibly utilize cache resources. Our design places log synchronization into a shared service, providing a novel solution for log sharing in storage-compute-separated databases. The architecture decouples functionality across modules, enabling elastic scaling where compute, cache, and storage resources can be resized rapidly and independently. Through experimental evaluation using multiple benchmark tests, including SysBench and TPC-H, we confirm that OceanBase Bacchus achieves performance comparable to or superior to that of HBase in OLTP scenarios and significantly outperforms StarRocks in OLAP workloads. Leveraging Bacchus's support for multi-cloud deployment and consistent performance, we not only retain high availability and competitive performance but also achieve substantial reductions in storage costs by 59% in OLTP scenarios and 89% in OLAP scenarios.