Data lakes and data warehouses are both very important for data analysis - and very different. Here's how to decide which you need.

In the ongoing debate about where companies ought to store data they want to analyze – in a data warehouses or in data lake — Databricks today unveiled a third way. With SQL Analytics, Databricks is ...

At the 2nd Annual Semantic Layer Summit, which took place April 26, AtScale founder and CTO Dave Mariani sat down with Bill Inmon, recognized by many as the father of the data warehouse, to discuss ...

The data lakehouse – it’s not a summer retreat for over-worked database administrators (DBAs) or data scientists, it’s a concept that tries to bridge the gap between the data warehouse and ...

A data lake isn't the same as a data warehouse and vice versa. The easy thing to do, IMO, is to evaluate whether what you want to do is one or the other and then proceeding from there. Just ...

A data lakehouse addresses these typical limitations of a data lake, as well as data warehouse architecture, by combining the best elements of data warehouses and data lakes to deliver significant ...

Data lakehouse architecture combines the best of cloud data lake and warehousing architectures to give teams the most recent data.

Part 5 of CRN’s 2023 Big Data 100 takes a look at the vendors solution providers should know in the data warehouse and data lake systems and services space.

Has the traditional data warehouse finally reached the end of its life? If so, what will follow it? Will it be a hybrid? We find out.

There are a few key differences between data warehouses and data lakes. Here’s what K–12 IT leaders should consider when looking at how they might address their schools’ data storage needs. What Are ...