IOMETE

IOMETE offers a self-hosted sovereign data lakehouse platform designed for AI-era data needs. It emphasizes on-premises, hybrid, or private cloud deployment with data ownership, security, and cost control, aiming to avoid vendor lock-in and SaaS price inflation.

A self-hosted data lakehouse platform that can run on-premises, in private cloud, public cloud, or hybrid environments. It includes a suite of components: data lakehouse, data catalog, SQL editor, data security at granular levels, Spark integration and orchestration, real-time data processing from sources like Kafka/Kinesis/Pulsar, a unified interface for Spark workloads, Jupyter notebook support, and a central data catalog with metadata, lineage, and quality information. It supports deployment across multiple cloud providers and offers features like Spark Connect, interactive notebooks, SQL tooling with autocompletion and visual explain plans, real-time processing, and customizable security controls down to user/role/column level.

Who it’s for: Enterprises and teams that require self-hosted, hybrid or on-prem data lakehouse solutions with strong data ownership, privacy, and security controls, including AI/ML workloads and large-scale data processing.

Hiring/traction mentions not explicit; emphasizes deployment flexibility, self-hosted controls, and an engineering-led approach