VAST bets on Apache Arrow as the open interface to structured data. By "bet," we mean that VAST does not work without Arrow. And we are not alone. Influx's IOx, DataDog's Husky, Anyscale's Ray, TensorBase, and others committed themselves to making Arrow a corner stone of their system architecture. For us, Arrow was not always a required dependency. We shifted to a tighter integration over the years as the Arrow ecosystem matured. In this blog post we explain our journey of becoming an Arrow-native engine.
Dear community, we are excited to announce VAST v2.0, bringing faster execution of bulk-submitted queries, improved tunability of index structures, and new configurability through environment variables.
Dear community, we are happy to announce the release of VAST v1.1.2, the latest release on the VAST v1.1 series. This release contains a fix for a race condition that could lead to VAST eventually becoming unresponsive to queries in large deployments.
Dear community, we are excited to announce VAST v1.1, which ships with exciting new features: query language plugins to exchange the query expression frontend, and compaction as a mechanism for expressing fine-grained data retention policies and gradually aging out data instead of simply deleting it.