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

In a certain sense, that’s true. Both databases and data warehouses store data that is queried in response to a search. However, databases are unitaskers, while data warehouses can answer complex ...

Data lakes, along with data warehouses and databases, are central to modern computing. They form building blocks for data transformation.

1. Data in data lakes is stored in its native format In a data lake, data can be loaded faster and accessed quicker since it does not need to go through an initial transformation process. For ...

Businesses large and small, along with data scientists, IT professionals and analysts, have been talking about the differences between databases and data lakes with increasingly vocal interest. But ...

A data warehouse contains structured data whereas a data lake can contain structured, unstructured, and semi-structured data. Data in the data lake comes from multiple sources and will have varying ...

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 ...

I work at a startup and our data is very messy at the moment, as you might imagine. We have a few product level transactional databases, but no central database to store it all in a useful way for ...

We asked experts to help us shed light on the differences between a data lake and a data warehouse and what that means for your organization.

This week CRN is running the Big Data 100 list in a series of slide shows, organized by technology category, spotlighting vendors of business analytics software, database systems, data warehouse ...