Data lakes and data warehouses are two of the most popular forms of data storage and processing platforms, both of which can be employed to improve a business’s use of information. However, these ...

A monthly overview of things you need to know as an architect or aspiring architect. Ramya Krishnamoorthy shares a detailed case study on rewriting Momento's high-performance data platform from Kotlin ...

The “data” part of the terms “data lake,” “data warehouse,” and “database” is easy enough to understand. Data are everywhere, and the bits need to be kept somewhere. But should they be stored in a ...

A data lake is not a direct replacement for a data warehouse; they are supplemental technologies that serve different use cases with some overlap. Most organizations that have a data lake will also ...

Data warehouse systems have been at the center of many big data initiatives going as far back as the 1980s. Today companies from leading cloud hyperscalers such as Amazon Web Services (Redshift) and ...

Enterprise data warehouses, or EDWs, are unified databases for all historical data across an enterprise, optimized for analytics. These days, organizations implementing data warehouses often consider ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. Data lakes are cool, but you don’t have to jump in head-first. It’s easy to start by dipping ...

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 ...

If you’re even tangentially involved with big data, you know that finding storage solutions for the volumes of data being generated every second is of utmost importance. When it comes to managing data ...

Data warehouses have been at the center of data analytics systems within many businesses and organizations for years, going as far back as the 1980s. With the growing adoption of cloud, data warehouse ...