Businesses often need to aggregate topics because it is essential for organizing, simplifying, and optimizing the processing of streaming data. It enables efficient analysis, facilitates modular development, and enhances the overall effectiveness of streaming applications. For example, if there are separate clusters, and there are topics with the same purpose in the different clusters, then it is useful to aggregate the content into one topic.

It’s hard to believe it’s been 15 years since the global financial crisis of 2007/2008. While this might be a blast from the past we’d rather leave in the proverbial rear-view mirror, in March of 2023 we were back to the future with the collapse of Silicon Valley Bank (SVB), the largest US bank to fail since 2008.

Apache Iceberg has recently grown in popularity because it adds data warehouse-like capabilities to your data lake making it easier to analyze all your data—structured and unstructured. It offers several benefits such as schema evolution, hidden partitioning, time travel, and more that improve the productivity of data engineers and data analysts. However, you need to regularly maintain Iceberg tables to keep them in a healthy state so that read queries can perform faster.

In the previous blog post we covered the high availability feature of Cloudera Operational Database (COD) in Amazon AWS. Cloudera recently released a new version of COD, which adds HA support to Microsoft Azure-based databases in the Cloud. In this post, we’ll perform a similar test to validate that the feature works as expected in Azure, too.

In Cloudera deployments on public cloud, one of the key configuration elements is the DNS. Get it wrong and your deployment may become wholly unusable with users unable to access and use the Cloudera data services. If the DNS is set up less ideal than it could be, connectivity and performance issues may arise. In this blog, we’ll take you through our tried and tested best practices for setting up your DNS for use with Cloudera on Azure.

This blog post describes support for materialized views for the Iceberg table format in Cloudera Data Warehouse. Apache Iceberg is a high-performance open table format for petabyte-scale analytic datasets. It has been designed and developed as an open community standard to ensure compatibility across languages and implementations.