![]() ![]() Physical data warehouses are complex and expensive to build and maintain, though.Ĭloud-based data warehouse services offer a much cheaper and easier way to use a data warehouse without needing any physical resources on site. Traditional on-premise data warehouses are used for analyzing an organization’s historical data in one unified repository, pulling data from many different source systems, such as operational databases. The comparison can also teach you what to look for in more general terms when considering any cloud-based data solution currently available. When you’re finished reading, you’ll know which service you should choose between Athena and Redshift. In this post, you’ll get a broad overview of cloud-based data warehousing, and you’ll come to understand the main differences between Amazon Redshift and Amazon Athena (also see this post by Panoply on the subject). However, with a dizzying amount of information available on both services, it’s a challenge to recognize what to look out for when choosing a cloud-based data service to meet your needs. Two popular AWS cloud computing services for data analytics and BI are Amazon Redshift and Amazon Athena, both of which are useful for delivering actionable insights that drive better decision making from your data. ( Note: This is a guest post from our friends at Panoply)Ĭloud-based data services are all the rage these days for many good reasons, and AWS (Amazon Web Services) is the current king of cloud-based data service providers, as this analysis carried out by StackOverflow indicates.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |