As little as 10 years ago the main database options to deploy a Data Warehouse were provided by Oracle, Microsoft and IBM using hardware installed on-premises, with a an expensive and inflexible license cost. Fast forward to today, and the market for Big Data and Analytics have exploded, and there’s a massive wave of innovation and disruption including Hadoop, Data Lakes, Real Time Analytics, and a wholesale migration of IT systems to The Cloud.

The Data Warehouse industry has not remained immune to upheaval, and according to Datanyze, Oracle, the previous market leader doesn’t even make the top 10 in terms of new sales and market share. Also, three of the market leaders (Amazon Redshift, Google Big Query and Snowflake), are all dedicated cloud based data warehouse solutions - all released in the last ten years.

My research indicates that cloud based analytic platforms come with compelling benefits of cost control and extreme agility, with the ability to provision a warehouse within minutes. In addition, some solutions can scale up (or down) within seconds, and produce a fully working multi-terabyte sized database copy within minutes.

To address this subject area, I’ve written an eBook Comparison of Cloud Data Warehouse Platforms, which is free to download. In this 26 page document, I explore how the selection criteria for an analytics database has changed, and compare solutions from a number of vendors against the ideal.

Options evaluated include Oracle, Microsoft, Amazon, Snowflake and Hadoop, and I think you’ll be genuinely surprised by the findings.

You’ll need to provide an eMail addresses to download the eBook, but it does mean you’ll receive further insightful articles on data warehouse technology directly to your mail-box, and yes, you can rest assured, you won’t be spammed with rubbish.

A Comparison of Cloud Data Warehouse Platforms

Disclaimer: The opinions expressed in my articles are my own and will not necessarily reflect those of my employer (past or present) or indeed any client I have worked with.