Cloudera, the former Hadoop startup that once soared with $1 billion in funding and went public in 2018 before being acquired by private equity for $5.3 billion in 2021, has now announced the acquisition of Verta, an AI startup specializing in machine learning model management, focusing on large language models used in generative AI.
Since launching a SaaS data lakehouse post-acquisition, Cloudera needed advanced AI capabilities to remain competitive in today’s market. CEO Charles Sansbury acknowledged this necessity.
“The future of data management is AI; they go hand-in-hand. Cloudera is acquiring Verta’s Operational AI platform to strengthen our team and accelerate our operational AI capabilities,” he said in a statement.
With the industry pivoting towards large language models, Verta transitioned from a task-based model management platform to one designed to manage these advanced models, essentially serving as a control center.
In an era when recruiting quality AI talent is challenging, this acquisition brings Cloudera top-tier professionals to enhance their AI tools. This includes co-founders CEO Manasi Vartak, an MIT CSAIL alum, and CTO Conrado Miranda, former machine learning lead at Twitter.
Founded in 2018, Verta raised nearly $16 million, according to Pitchbook, encompassing a $10 million Series A round in 2020. Vartak initially developed the open-source ModelDB database in graduate school as a version tracking system for machine models, which later evolved into Verta.
Cloudera began as a Hadoop startup in 2008, during the early days of large-scale data processing, using Hadoop—an open-source project first developed at Yahoo in 2005—as the cutting-edge solution. However, by the time Cloudera went public, newer, simpler, and more cost-effective data processing methods had eclipsed Hadoop.
Simultaneously, companies were migrating their data workloads to the cloud—be it giants like Amazon, Microsoft, and Google, or emerging firms like Snowflake and Databricks. Despite its name, Cloudera’s solutions were primarily on-premises for much of its history.
Building a SaaS data lakehouse in 2021 was partly a strategy to compete with cloud-native organizations. Since then, both Databricks and Snowflake have integrated AI capabilities, both organically and through acquisitions.
Today’s acquisition is a strategic move to stay competitive.
