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Data lakes vs. data warehouses: Decoding the data storage debate

Data Science Dojo

When it comes to data, there are two main types: data lakes and data warehouses. Which one is right for your business? What is a data lake? An enormous amount of raw data is stored in its original format in a data lake until it is required for analytics applications.

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What Is a Lakebase?

databricks

Published: June 11, 2025 Announcements 5 min read by Ali Ghodsi , Stas Kelvich , Heikki Linnakangas , Nikita Shamgunov , Arsalan Tavakoli-Shiraji , Patrick Wendell , Reynold Xin and Matei Zaharia Share this post Keep up with us Subscribe Summary Operational databases were not designed for today’s AI-driven applications.

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Data Version Control for Data Lakes: Handling the Changes in Large Scale

ODSC - Open Data Science

In the ever-evolving world of big data, managing vast amounts of information efficiently has become a critical challenge for businesses across the globe. Understanding Data Lakes A data lake is a centralized repository that stores structured, semi-structured, and unstructured data in its raw format.

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Build a financial research assistant using Amazon Q Business and Amazon QuickSight for generative AI–powered insights

Flipboard

Their information is split between two types of data: unstructured data (such as PDFs, HTML pages, and documents) and structured data (such as databases, data lakes, and real-time reports). Different types of data typically require different tools to access them.

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Data Integrity for AI: What’s Old is New Again

Precisely

Data marts involved the creation of built-for-purpose analytic repositories meant to directly support more specific business users and reporting needs (e.g., But those end users werent always clear on which data they should use for which reports, as the data definitions were often unclear or conflicting. A data lake!

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Query structured data from Amazon Q Business using Amazon QuickSight integration

AWS Machine Learning Blog

Although generative AI is fueling transformative innovations, enterprises may still experience sharply divided data silos when it comes to enterprise knowledge, in particular between unstructured content (such as PDFs, Word documents, and HTML pages), and structured data (real-time data and reports stored in databases or data lakes).

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Data Lakes Vs. Data Warehouse: Its significance and relevance in the data world

Pickl AI

Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.