Researchers from MIT and other institutions report that a “hash function” — a core database search operation — can be significantly accelerated through the use of machine learning. The hope is that the new technique could accelerate computational systems that scientists use to store and analyze DNA, amino acid sequences, or other biological information.
MIT: New Method Uses ML to Accelerate Data Retrieval in Large Databases
Kinetica Database Now on Azure
October 12, 2021 – Database company Kinetica is now accessible as a service on the Microsoft Azure cloud platform, designed to give organizations real-time contextual analysis and location intelligence on massive data sets with reduced computing infrastructure and lower costs. Kinetica’s vectorized database is used to analyze data from sensors and machines in real time. For […]
The Race for a Unified Analytics Warehouse
This white paper from our friends over at Vertica discusses how the race for a unified analytics warehouse is on. The data warehouse has been around for almost three decades. Shortly after big data platforms were introduced in the late 2000s, there was talk that the data warehouse was dead—but it never went away. When big data platform vendors realized that the data warehouse was here to stay, they started building databases on top of their file system and conceptualizing a data lake that would replace the data warehouse. It never did.