IOMETE
IOMETE is a self-hosted data lakehouse platform built on Apache Iceberg, Apache Spark, and Kubernetes. Run it on-premises or in your private cloud — your infrastructure, your data, your control.
Built for enterprises in regulated industries, IOMETE eliminates third-party ICT risk at the data layer by architecture — not by contract. No SaaS dependencies. No data leaving your perimeter. Compliance with GDPR, DORA, and NIS2 is structural, not contractual.
Included in one platform:
- Data Lakehouse(s)
- Data Catalog
- SQL Editor
- Apache Spark Jobs
- ML Notebooks
- Orchestration Engine
- Spark Connect
Key capabilities: Apache Iceberg-native storage, Kubernetes-native deployment (K8s + OpenShift), row/column/tag-based access control, Data Mesh support, air-gapped and zero-trust compatible.
Transparent pricing — CPU-based, no per-query fees, no billing surprises.
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Google Cloud Managed Service for Apache Spark
Managed Service for Apache Spark is a Google Cloud solution that simplifies running Apache Spark workloads with either serverless execution or fully managed clusters. It allows users to process large-scale data without needing to manage infrastructure, reducing operational complexity. The platform features Lightning Engine, which accelerates Spark performance by up to 4.9 times compared to open-source Spark. It supports data engineering, data science, and machine learning workflows at scale. Integration with Gemini enables AI-powered development, including automated code generation and troubleshooting. The service works seamlessly with open data formats like Apache Iceberg and integrates with tools like BigQuery and Knowledge Catalog. It offers flexible deployment options to suit different workloads and use cases. Overall, it provides a faster, smarter, and more efficient way to run Spark workloads in the cloud.
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Azure Blob Storage
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Amazon Redshift
Amazon Redshift is a cloud-based data warehouse solution from AWS designed to deliver high-performance analytics and support modern AI-driven workloads. The platform enables organizations to analyze large volumes of structured and unstructured data across data warehouses, data lakes, and third-party sources using SQL. Redshift is built for scalability and cost efficiency, offering improved throughput and price-performance with AWS Graviton-powered RG instances and Redshift Serverless options. The solution also supports near real-time analytics through zero-ETL integrations that connect operational databases, streaming services, and enterprise applications without complex data pipelines. Amazon Redshift integrates with Amazon SageMaker and Amazon Bedrock to support advanced machine learning, analytics, and generative AI use cases.
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