November 2019 Summaries

Typical ad-hoc analytical queries have to process much more data than can fit in memory, leading to I/O bound performance issues. The Analytics service in Couchbase 6.0 allows users to specify multiple "Analytics Disk Paths" during node initialization, enabling the partitioning of data across all specified paths in all nodes with the Analytics service. This feature can significantly speed up Analytics queries by utilizing modern storage devices like SSDs and concurrent reads. When a single "Analytics Disk Path" is specified, the Analytics service automatically creates multiple data partitions within the same storage device to optimize performance. Experiments have shown that this automatic configuration option can lead to substantial improvements in query response times, particularly when using high-performance storage devices like NVMe SSDs. By utilizing multiple physical disks and optimizing I/O operations, the Analytics engine can achieve significant performance gains, especially for large-scale data sets. The results demonstrate the importance of carefully configuring "Analytics Disk Paths" to maximize the performance impact of the Analytics service.

The article provides a detailed guide on establishing a connection between Couchbase Analytics and SQL Server using the CData ODBC driver. It outlines the prerequisites, including the necessity of a Couchbase Server Enterprise Edition cluster with Data and Analytic services enabled, and the installation of SQL Server Express. The setup process involves configuring Couchbase with sample data and creating shadow datasets for analysis, followed by the installation and configuration of the CData ODBC Driver for Couchbase. The guide also covers setting up the CData SQL Gateway to enable SQL Server Linked Server functionality, allowing users to execute SQL statements in SQL Server Management Studio that interact with Couchbase Analytics. It encourages users to further explore data integration by creating tables and inserting data from Couchbase into SQL Server, leveraging the extended analytics capabilities provided by CData drivers.

This article explores the use of ASP.NET Core Microservices, specifically a Database per service pattern, using Docker (docker-compose) as an orchestration tool. The author creates a new solution in Visual Studio and sets up a basic ASP.NET Core project with Docker support. They then add a Couchbase database to the project using Docker Compose, configuring the database and making it accessible to the application. The article concludes with steps for using the database, exploring volumes, automation options, and considerations for deploying to Kubernetes.