Dremio, the unified lakehouse platform for self-service analytics and AI, unveiled new capabilities that keep Apache Iceberg lakehouse flexible, fast, and easy-to-use for every data environment. Dremio announced collaborations that bring the lakehouse to every environment for all of a customer’s data. Additionally, Dremio revealed capabilities that will further enhance its price-performant SQL engine, making it faster, easier to use, and more broadly integrated across the Analytics and AI ecosystem.
Highlights of the Announcement
- STACKITDremio expanded its Apache Iceberg lakehouse to suit any environment, whether cloud, on premises, or hybrid, including highly regulated, Air Gap network secured, or data sovereignty governed settings. Dremio also announced VAST Data (which introduces the Zero Trust Lakehouse Platform with Dremio) and (which offers European organizations a fully-managed open lakehouse platform service to meet stringent data residency requirements).
- The company’s SQL engine for Iceberg achieves sub-second BI with Reflections Query Acceleration technology. Enhancements include recommendations for optimal query acceleration usage, scheduled Reflections for up-to-date data access, and incremental updates for streamlined management and cost reduction, advancing towards autonomous Reflections.
- Dremio has incorporated Nessie into Dremio Software, adding to the managed Nessie capabilities already in Dremio Cloud. These capabilities simplify data engineering with Git-like workflows on lakehouse data, enabling users to run production workloads with end-to-end Dremio support for a Nessie-native Apache Iceberg catalog.
- Newly introduced generative AI capabilities to streamline data discovery and analysis in the Dremio Platform. GenAI Text-to-SQL enables intuitive querying through natural language, while advanced generative AI-driven data descriptions and labeling facilitate fast, accurate data discovery and curation. Partnerships with AI and ML Ops companies such as Dataiku and DataRobot allow Dremio to accelerate the AI life cycle, from Dremio’s Git-like data versioning to enable rapid experimentation and model reproducibility through to operability with these AI and ML solutions.
- Dremio also announced support for AWS Graviton in Preview. The new engine configurations instantly deliver a performance boost and cost savings for users.
Read the full article via TDWI.
