MariaDB ColumnStore is a massively parallel scale out columnar database. Data loading and modification behaves somewhat differently from how a row based engine works. This article outlines the options available and how these affect performance.
MariaDB ColumnStore is a massively parallel scale out columnar database. Query execution behaves quite differently from how a row-based engine works. This article outlines how queries are executed, optimized, and how performance can be influenced.
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MariaDB ColumnStore user Andrew Ernst from the Institute for Health Metrics and Evaluation discusses how other storage engines have "failed miserably" and why he chose ColumnStore instead.
I am happy to announce the general availability of MariaDB ColumnStore 1.0!
MariaDB ColumnStore is a powerful open source columnar storage engine that unites transactional and analytic processing with a single ANSI SQL front end to deliver a solution that simplifies high-performance, big data analytics.
Today, MariaDB ColumnStore has reached a major milestone – MariaDB ColumnStore 1.0 is now GA with the release of MariaDB ColumnStore 1.0.6 GA. The journey of MariaDB ColumnStore began in January 2016 when our team started building ColumnStore. The support from our early alpha and beta adopters and community users has helped us take MariaDB ColumnStore from the first alpha release to the GA today.
In this blog post, I will outline MariaDB ColumnStore's architecture, which has the capacity to handle large datasets and scale out across multiple nodes as your data grows.
With the recent announcement of MariaDB ColumnStore, we get many questions on the architecture and functionality of MariaDB ColumnStore. This blog post describes the architecture of MariaDB ColumnStore.
Today, MariaDB ColumnStore, MariaDB's distributed columnar storage engine for analytics workload, is reaching its next major milestone – the availability of MariaDB ColumnStore 1.0.4 Beta software release.
MariaDB ColumnStore is built on a three-tier scalable architecture that supports the kind of growth that MariaDB users have grown accustomed to. Queries are processed by user modules, which assign tasks to parallel performance modules that access the columnar distributed storage layer below. Performance modules scale almost infinitely, providing both performance and capacity growth as you add servers. They also provide built-in data redundancy. These modules don’t process queries; they just take instructions from the user modules, which organize and deliver the results.