Performance is one of the key, if not the most important deciding criterion, in choosing a Cloud Data Warehouse service. In today’s fast changing world, enterprises have to make data driven decisions quickly and for that they rely heavily on their data warehouse service. In this blog post, we compare Cloudera Data Warehouse (CDW) on Cloudera Data Platform (CDP) using Apache Hive-LLAP to Microsoft HDInsight (also powered by Apache Hive-LLAP) on Azure using the TPC-DS 2.9 benchmark.

Some of the most powerful results come from combining complementary superpowers, and the “dynamic duo” of Apache Hive LLAP and Apache Impala, both included in Cloudera Data Warehouse, is further evidence of this. Both Impala and Hive can operate at an unprecedented and massive scale, with many petabytes of data. Both are 100% Open source, so you can avoid vendor lock-in while you use your favorite BI tools, and benefit from community-driven innovation.

The Cloudera Data Warehouse (CDW) service is a managed data warehouse that runs Cloudera’s powerful engines on a containerized architecture. It is part of the new Cloudera Data Platform, or CDP, which went live on Microsoft Azure earlier this year. The CDW service lets you meet SLAs, onboard new use cases with zero friction, and minimize cost. Today, we are pleased to announce the general availability of CDW on Microsoft Azure.

When migrating a data warehouse to BigQuery, one of the most critical tasks is mapping existing user permissions to equivalent Google Cloud Identity and Access Management (Cloud IAM) permissions and roles. This is especially true for migrating from large enterprise data warehouses like Teradata to BigQuery. The existing Teradata databases commonly contain multiple user-defined roles that combine access permissions and capture common data access patterns.