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.

How enterprise-grade data management creates better and more efficient care. In the last few years, the acceptance of telehealth has become more widespread as patients and providers found they could maintain continuity through phone and video collaboration, instead of in-person visits. In many cases, a level of care that once required a drive to the clinic or hospital could be delivered over a mobile phone or laptop, with no travel and no waiting room.

Forrester Research recently released the Forester Wave for Streaming Platforms, Q4 2023. We are happy to share that Cloudera ranked as a strong performer, with a top three score for current offering. This score was stronger than anyone outside of one-cloud vendors Microsoft and Google, including a stronger current offering than Confluent. Cloudera is also the strongest on-prem offering and the only fully hybrid offering to achieve a strong performer score.

Delivering transformational innovation and accurate business decisions requires harnessing the full potential of your organization’s entire data ecosystem. Ultimately, this boils down to how reliable and trustworthy the underlying data that feeds your insights and applications is. This applies to modern generative AI solutions that are particularly reliant on trusted, accurate, and context-specific data.

Replication is a crucial capability in distributed systems to address challenges related to fault tolerance, high availability, load balancing, scalability, data locality, network efficiency, and data durability. It forms a foundational element for building robust and reliable distributed architectures. It is also important to have multiple options (like normal and prefixless replication) to do the replication process, since every solution has its own advantages.

In the dynamic landscape of modern manufacturing, AI has emerged as a transformative differentiator, reshaping the industry for those seeking the competitive advantages of gained efficiency and innovation. As we navigate the fourth and fifth industrial revolution, AI technologies are catalyzing a paradigm shift in how products are designed, produced, and optimized.