Excerpt of What Gartner Sees In Analytic Hubs published January 29, 2019 by Alex Woodie for Datanami.
In the old days, companies would build their business intelligence strategies from the ground up, typically starting with a traditional data warehouse. But as the volume, trajectory, and types of data have exploded, companies have looked for more agile solutions to drive their analytics strategies. The state of the art in this software genre is something that Gartner calls a data management solution for analytics (DMSA), or an “analytics hub.”
According to Gartner, a DMSA is a “complete software system that supports and manages data in one or many file management systems, most commonly a database or multiple databases.” Depending on the underlying data model used – such as relational, XML, JSON, key-value, geospatial, or graph — a DMSA can take on many different flavors, including traditional SQL analytics, machine learning, or graph processing.
Gartner grouped the Hadoop DMSA vendors – Cloudera, MapR and Hortonworks (which has since merged with Cloudera) – into its own cohort within the Challenger’s Quadrant. These vendors have strengths in supporting data lakes and context-independent use cases, Gartner says, but struggle to meet requirements for traditional data warehouses and have yet to complete the transition to the cloud.
A second cohort of Challengers consists of emerging Chinese firms, including Alibaba Cloud, GBase, and Huawei. While Gartner considers their products “generally capable,” they remain mostly used in the Asia Pacific region, and face headwinds for use in North America and Europe, the analyst firm says.
Neo4j is another challenger with a strong story to tell in one area: Graph processing. Gartner says Neo4j is the dominant vendor in graph, and likes how easy it is for customers to get started. But limited applicability outside of graph lowered its DMSA marks.