As modern query engines like Spark and Trino replaced Hadoop, organizations turned away from HDFS and DAS-based architectures in favor of object storage based on AWS S3. However, S3's lower performance required query engines to introduce workarounds, such as caching middleware, which greatly complicated architectures.

Introducing VAST DataBase, a high-speed transactional and analytical database that can handle millions of transactions per second and terabytes per second of query throughput at exabyte-scale. Designed to run at the edge, core, and cloud, the VAST DataBase enables organizations to capture data in real-time, archive it at data lake scale, and perform queries on real-time streaming data across exascale datasets. Without the need for separate databases, data warehouses, data lake platforms, or complex ETL pipelines, it's now possible to deliver insights faster and at lower TCO than ever before.

VAST solves the challenges of performance and scale for open platform analytics with scale-out NFS that provides parallel file systems levels of performance. Cloud-native applications benefit from VAST’s high-performance S3 implementation combined with full multiprotocol interoperability.  Managing data at scale is simple with the VAST Catalog, an always-in-sync automatic metadata index built on the VAST DataBase that lets you search and find data via intuitive UI and SQL interface for advanced queries and automating workflows.

The VAST Data Platform is a revolutionary architecture built for the era of deep learning. Providing predictable, real-time performance with the capacity to support thousands of queries simultaneously at the scale needed for query engines to be able to randomly read across massive data sets.