Data Lakehouses

A collection of 15 posts tagged with "Data Lakehouses"

Major global electric utility provider delivers modern smart meter data lakehouse powered by AIStor

David Koppe David Koppe on Case Study |
Major global electric utility provider delivers modern smart meter data lakehouse powered by AIStor

Our customer, a large electric utility company with millions of users, was faced with challenges common to utility and energy companies around the world: how to manage ever-growing energy demands, while diversifying energy supply to incorporate renewable and sustainable sources. A key element of their strategy is a smart metering initiative - bringing the power of technology and AI to

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A Global Telecommunications Leader and MinIO AIStor: Powering the Next Generation of Data Lakehouse for Analytics and AI

David Koppe David Koppe on Case Study |
A Global Telecommunications Leader and MinIO AIStor: Powering the Next Generation of Data Lakehouse for Analytics and AI

1. Executive Summary Our customer, a global telecommunications leader, established a Data Platform team to transform how data improved customer experiences and business operations. Faced with ballooning data growth and legacy storage constraints, they replaced aging legacy data storage systems with a high-performance, cloud-native data lakehouse, built on MinIO’s AIStor. The result: a scalable, cost-efficient foundation ready for AI,

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Hadoop HDFS's Logical Successor

MinIO MinIO MinIO on Performance |
Hadoop HDFS's Logical Successor

The "big data king" that enterprises spent billions on is dying. Not from lack of trying, but because cloud-native alternatives now beat it at its own game. AIStor is faster and cheaper than HDFS. The revolution is happening in quarters, not decades.

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From Data Swamps to Reliable Data Systems: How Iceberg Brought 40 Years of Database Wisdom to Data Lakes

From Data Swamps to Reliable Data Systems: How Iceberg Brought 40 Years of Database Wisdom to Data Lakes

The data lake was once heralded as the future, an infinitely scalable reservoir for all our raw data, promising to transform it into actionable insights. This was a logical progression from databases and data warehouses, each step driven by the increasing demand for scalability. Yet, in embracing the data lake's scale and flexibility, we overlooked a critical difference.

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