Couchbase Capella is a scalable document-oriented database service in the cloud. Its existing Capella Operational service is based on a shared-nothing architecture and supports high volumes of low-latency queries and updates for JSON documents. Its new Capella Columnar cloud service complements the Operational service. The Capella Columnar service supports complex analytical queries (e.g., ad hoc joins and aggregations) over large collections of JSON documents that can originate from a variety of Couchbase and non-Couchbase data sources and formats and can either be stored and managed by the Capella Columnar service or externally stored and accessed on demand at query time. This paper describes the new Capella Columnar service, looking both over and under the hood.

Database management systems that support hybrid workloads (i.e., HTAP or HOAP) first arose in the relational world. Such hybrid data management support in the document database (NoSQL) world is also gaining popularity in both commercial and research arenas. The CH2 benchmark was proposed in 2021 to evaluate such hybrid NoSQL platforms. In addition to operational and analytical services, full-text search is a key component of NoSQL platforms that provides a search engine-like query processing capability on JSON documents. In this paper, we present CH3, a mixed workload benchmark for evaluating scalable NoSQL platforms with OLTP, OLAP, and full-text search (FTS) workloads. Like CH2, the CH3 benchmark borrows from and extends both TPC-C and TPC-H. However, CH3 generates meaningful text content and includes FTS indexes and FTS queries on these indexes to model an FTS workload. This paper presents the required extensions from CH2 to address FTS workloads, the detailed design of CH3, and performance results obtained by running the CH3 benchmark against Couchbase Server (which offers Query, Analytics, and Search Services). The results provide insight into the performance of the Search Service, the performance isolation among OLTP, OLAP and FTS workloads, and the horizontal scalability of Couchbase Server as well as the effectiveness of CH3 for evaluating the mixed workload performance of such NoSQL platforms.

Huawei Fusion Insight Libr A (FI-MPPDB) is a petabyte scale enterprise analytics platform developed by the Huawei data-base group. It started as a prototype more than five years ago, and is now being used by many enterprise customers over the globe, including some of the world's largest financial institutions. Our product direction and enhancements have been mainly driven by customer requirements in the fast evolving Chinese market. This paper describes the architecture of FI-MPPDB and some of its major enhancements. In particular, we focus on top four requirements from our customers related to data analytics on the cloud: system availability, auto tuning, query over heterogeneous data models on the cloud, and the ability to utilize powerful modern hardware for good performance. We present our latest advancements in the above areas including online expansion, auto tuning in query optimizer, SQL on HDFS, and intelligent JIT compiled execution. Finally, we present some experimental results to demonstrate the effectiveness of these technologies.