About the Documentation for Datometry on Microsoft Azure
The Datometry documentation provides guidance on the implementation and usage of Datometry® Hyper-Q™ for Microsoft Azure.
Learn About Our Documentation
The Datometry documentation consists of the following user guides.
Datometry Concepts and Features: An introduction to Datometry solutions and how they work together to enable you to re-platform your existing, on-premise data warehouse to a cloud-based data warehouse such as Microsoft Azure Synapse Analytics.
Hyper-Q Database and Client Software Compatibility: Hyper-Q is compatible with the following databases, client software, drivers, and operating systems.
Hyper-Q for Azure Synapse Installation and Setup: A guide to help you plan, install, and configure Hyper-Q for use with Microsoft Azure Synapse Analytics.
Hyper-Q Configuration for Azure Synapse: You can configure Hyper-Q for your specific deployment using the Hyper-Q configuration file.
Hyper-Q Monitoring for Azure Synapse Analytics: You can configure Hyper-Q logging and monitoring for use with Microsoft Azure Synapse Analytics and the InfluxData Telegraf data collector.
Configuring your Azure environment to collect Hyper-Q log entries and metrics, and provide alerts based on operational and performance issues, lets you provide effective operations support.
Hyper-Q SQL Hints: A SQL hint instructs the database engine on how to execute a query. For example, a hint may tell the query optimizer to use or not to use an index, even if the query optimizer would decide otherwise. Hyper-Q hints provide a mechanism to instruct the query optimizer to choose a certain query execution plan based on specific criteria.
Intended Audience
This document is intended for experienced Linux system administrators who are familiar with Microsoft Azure, Azure Synapse Analytics, and data center operations.
To learn about Microsoft Azure, see the Microsoft Azure documentation.
Copyright Notice
Copyright © 2021–2023 Datometry Inc., All rights reserved.
Datometry believes the information in this publication to be accurate as of its publication date. The information is subject to change without notice.
THE INFORMATION IN THIS PUBLICATION IS PROVIDED “AS IS.” Datometry MAKES NO REPRESENTATIONS OR WARRANTIES OF ANY KIND WITH RESPECT TO THE INFORMATION IN THIS PUBLICATION, AND SPECIFICALLY DISCLAIMS IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE.
Use, copying, and distribution of any Datometry software described in this publication requires an applicable software license.
Datometry and Datometry Hyper-Q are trademarks of Datometry Inc. All other trademarks used herein are the property of their respective owners.