Hadoop was once the backbone of big data infrastructure, but in today’s world of real-time analytics and AI-driven applications, its limitations are impossible to ignore.
Architected for an era of spinning disks and batch workloads, Hadoop now imposes significant cost, complexity, and performance challenges. From bloated hardware footprints and high power consumption to rigid scaling models and outdated data protection methods, Hadoop is holding enterprises back just as data becomes their most valuable asset.
In our new white paper, Hadoop Modernization with the VAST Data Platform, we explore why now is the time to move beyond Hadoop and how VAST offers a future-ready alternative. VAST solves Hadoop’s inefficiencies with a highly scalable and performant platform that supports real-time ingestion and unifies access across file, object, and table formats - and moreover, enables organizations to consolidate a highly fragmented big data ecosystem.
So what does modernization actually look like? New findings from the white paper offer a glimpse:
Trino acceleration: Compared to S3-based queries, VAST processes selective queries up to 13x faster while reducing compute overhead.
Table updates at scale: No performance degradation – The VAST DataBase, one component of the VAST Data Platform, delivers consistent, sub-second table update performance, even as the number of tables scales
Big TCO savings – Thanks to data efficiency breakthroughs including Similarity reduction, locally decodable erasure codes, VAST drives down total cost of ownership by more than 60 percent across a six-year period.
These gains aren’t just theoretical. They’re real outcomes from organizations that have made the move. Hadoop was built for a different era. As businesses embrace AI and real-time data, modernization isn’t a matter of if, but how soon.
Read the full whitepaper to see how organizations are moving into the future of data.
