Big data vendor Cloudera is growing its portfolio with a series of efforts aimed at enabling a DataOps model.
Earlier this month, the company, based in Santa Clara, Calif., announced new and upcoming features for its Cloudera Data Platform, including Cloudera Data Engineering and Cloudera Data Visualization. The Data Engineering service makes use of Apache Spark for data queries and the Apache Airflow platform for workflow monitoring. The Data Visualization offering is based on technology that comes from Cloudera’s 2019 acquisition of Arcadia Data, which provides reporting and charting functionality.
Cloudera Data Engineering is generally available now; Cloudera Data Visualization is in technical preview.
According to Doug Henschen, an analyst at Constellation Research, Cloudera makes a good case for the breadth and depth of capabilities it can deliver without the heavy lifting of knitting together multiple point solutions, like databases, analytics environments and streaming tools. That said, he added that Cloudera also knows it still has work to do on simplifying its platform to lower the cost of ownership and maximize value for customers looking to support data engineering, as well as data science, data warehousing and operational database use cases.
How Cloudera Data Engineering enables DataOps