This week's list shines a light on the companies with the most impressive, vast and innovative data lake storage systems today, including AWS, IBM & Google
A data lake is a centralised storage repository that can hold vast amounts of raw data in its native format until it is needed for analysis.
Unlike traditional data warehouses that require data to be structured and processed before storage, data lakes can accommodate structured, semi-structured and unstructured data from a variety of sources.
In essence, this makes data lakes perfect for organisations that have huge portfolios of data and need flexible solutions when it comes to storage, even if they are unsure how they will use that data in the future.
In 2025, data lakes have become the darling of AI companies, whose technologies simply would not work without massive amounts of data.
In recent years the maturation of the 'lakehouse' architecture, a hybrid model that fuses the raw flexibility of data lakes with the transactional integrity of data warehouses, has been especially important to the AI sector.
Modern AI requires both colossal scale and unwavering data reliability, a combination that traditional architecture simply cannot provide.
In this week’s Top 10, we dive right into data lakes, spotlighting some of the best examples in terms of architecture and application.
10. Dremio
Founded: 2015
HQ: Santa Clara, California, USA
CEO: Sendur Sellakumar
Notable feature: A high-performance SQL query engine that queries data directly on the lake, eliminating data copies.
Read the full story, via AI Magazine.
