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Data lakes have been built with a desire to democratize data — to allow more and more people, tools, and applications to make use of more and more data. A key capability needed to achieve this is hiding the complexity of underlying data structures and physical data storage from users. The de facto standard to achieve this has been the Hive table format, released by Facebook in 2009 that addresses
The data landscape is a constantly changing one. We started with relational databases to store and process transactional data that was generated by a business’s day-to-day operations (e.g., customer, order details) to serve OLTP use cases. Then, with the rising need to derive analytical insights from a business’s stored data (e.g., average sales over time), we moved onto OLAP-based systems with da
Survey Report 2024 State of the Data Lakehouse Gain unprecedented insights into the evolving landscape of data lakehouses and benchmark your organization with Dremio's State of the Data Lakehouse Survey Report. This survey of 500 full-time IT and data professionals from large enterprises offers fresh insights on data lakehouse trends, adoption and associated benefits.
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