Today’s enterprise data analytics teams are constantly looking to get the best out of their platforms. Storage plays one of the most important roles in the data platforms strategy, it provides the basis for all compute engines and applications to be built on top of it. Businesses are also looking to move to a scale-out storage model that provides dense storages along with reliability, scalability, and performance.

Adobe is a legendary Silicon Valley company. From the desktop publishing era of the 1980s, powered by the Adobe Postscript page description language, through the creation and marketing of Photoshop, Illustrator, and other creative power tools, the digital revolution is unthinkable without Adobe.

Like most of our customers, Cloudera’s internal operations rely heavily on data. For more than a decade, Cloudera has built internal tools and data analysis primarily on a single production CDH cluster. This cluster runs workloads for every department – from real-time user interfaces for Support to providing recommendations in the Cloudera Data Platform (CDP) Upgrade Advisor to analyzing our business and closing our books.

What is Streaming Analytics? Streaming Analytics is a type of data analysis that processes data streams for real-time analytics. It continuously processes data from multiple streams and performs simple calculations to complex event processing for delivering sophisticated use cases. The primary purpose is to present the most up-to-date operational events for the user to stay on top of the business needs and take action as changes happen in real-time.

Many people wonder if they should use BigQuery or Bigtable. While these two services have a number of similarities, including "Big" in their names, they support very different use cases in your big data ecosystem. At a high level, Bigtable is a NoSQL wide-column database. It's optimized for low latency, large numbers of reads and writes, and maintaining performance at scale.