Remove Cost-Benefit Remove Data Lake Remove Interactive Remove Online Analytical Processing
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Build an Amazon Redshift data warehouse using an Amazon DynamoDB single-table design

AWS Big Data

In traditional databases, we would model such applications using a normalized data model (entity-relation diagram). A key pillar of AWS’s modern data strategy is the use of purpose-built data stores for specific use cases to achieve performance, cost, and scale. These types of queries are suited for a data warehouse.

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Unlocking Data Storage: The Traditional Data Warehouse vs. Cloud Data Warehouse

Sisense

While the architecture of traditional data warehouses and cloud data warehouses does differ, the ways in which data professionals interact with them (via SQL or SQL-like languages) is roughly the same. The primary differentiator is the data workload they serve. with a cloud data warehouse is simple.

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Unleashing the power of Presto: The Uber case study

IBM Big Data Hub

Presto is an open source distributed SQL query engine for data analytics and the data lakehouse, designed for running interactive analytic queries against datasets of all sizes, from gigabytes to petabytes. It excels in scalability and supports a wide range of analytical use cases.

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