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Insights and inspiration, case studies and community for AI/ML and Data Engineers.

Apache NiFi – designed for extension at scale

Apache NiFi – designed for extension at scale

AI systems need data all along the spectrum of unstructured, structured, and multi-modal.  The protocols by which these diverse types of data are both acquired and delivered are as varied as the data types themselves.  At the same time data volumes and latency requirements grow ever stronger which demands solutions which scale down and up first – then out.  In other words we need maximum efficiency, we can’t resort to remote procedure calls for every operation, and we need to support hundreds if not thousands of different components or tools in the same virtual machine.

Custom code adds risk to the enterprise

Custom code adds risk to the enterprise

Data teams are actively delivering new architectures to propel AI innovation at a rapid pace. In this blog, we’ll explore how Datavolo empowers these teams to accelerate while addressing the critical aspects of security, observability, and maintenance for their data...