The sovereign lakehouse
alternative to Starburst.
Starburst federates SQL across your existing sources with Trino. IOMETE goes further – a complete, self-hosted data lakehouse that runs SQL, ETL, ML, and streaming on one engine, entirely inside your infrastructure.
A complete lakehouse versus a query engine.
| Capability | IOMETE | Starburst |
|---|---|---|
| Core engine | Apache Spark – one engine for SQL, ETL, ML, and streaming | Trino – distributed SQL query and federation engine |
| Primary role | Complete data lakehouse: storage, compute, and governance | Query federation layer across existing data sources |
| Table format | Apache Iceberg-native managed storage | Iceberg plus many query-time connectors |
| ETL & data engineering | Native Spark jobs with built-in orchestration | Handled through external tools |
| ML & data science | Native notebooks in Python, R, and SQL | Not native – external frameworks required |
| Streaming ingestion | Native via Spark (Kafka, Kinesis, Pulsar) | Not native |
| Deployment | Fully self-hosted, Kubernetes-native | Self-hosted (Enterprise) or Galaxy SaaS |
| Control plane | Entirely within your infrastructure | Self-managed, or vendor-managed on Galaxy |
| Governance | Row, column, and tag policies enforced at query time in your perimeter | Built-in role-based access control |
| Compliance fit | SOC 2, HIPAA, GDPR; air-gapped capable | Enterprise security with federal options |
Starburst is excellent for federated SQL across many existing sources. IOMETE is the better fit when you want a complete, self-hosted lakehouse – storage, governance, SQL, ETL, ML, and streaming on one engine, fully in your infrastructure.
Built to own your data, end to end.
SQL, ETL, ML, and streaming on a single Spark engine
IOMETE runs every workload on one Apache Spark engine over Iceberg tables – one security model, one operational playbook. Starburst's Trino is a SQL query and federation layer, so ETL, ML, and streaming live in separate tools.
The control plane stays inside your infrastructure
Catalogs, governance, audit logs, and cluster definitions never leave your environment. There is no IOMETE data plane outside your network – clean DORA, HIPAA, and GDPR documentation, and air-gapped deployment when you need it.
Storage and compute, not just a query layer
IOMETE manages your Apache Iceberg tables with ACID transactions, time travel, and schema evolution – a full lakehouse. Starburst federates queries across sources you still operate and store elsewhere.
The cornerstone of our security strategy is our unique self-hosted architecture.
IOMETE operates entirely within the customer’s trust perimeter, whether on-premises or in the customer’s cloud account. This setup ensures that customers maintain complete control and ownership of their data.
By minimizing data movement, we not only reduce costs but also significantly lower the risk of data leaks or loss, while preventing vendor lock-in. Thanks to IOMETE’s unique self-hosted architecture, it’s impossible for us to lose your data simply because it is stored in your trusted environment.
Common questions about IOMETE vs Starburst.
What is the main difference between IOMETE and Starburst?
IOMETE is a complete, self-hosted data lakehouse – it manages your Apache Iceberg storage and runs SQL, ETL, ML, and streaming on a single Apache Spark engine. Starburst is built on Trino, a distributed SQL query and federation engine that queries data across sources you store and operate elsewhere.
Is Starburst a data lakehouse?
Starburst (Trino) is primarily a query and federation layer rather than a storage platform. It excels at running SQL across many existing systems. IOMETE is a full lakehouse: it owns ACID Iceberg table management, governance, and compute together.
Can IOMETE run fully on-premises or air-gapped?
Yes. IOMETE deploys entirely inside your Kubernetes infrastructure — on-premises, sovereign cloud, or private cloud — with no IOMETE data plane outside your network. It supports air-gapped environments for defense, government, and highly regulated workloads.
Does IOMETE support machine learning and streaming natively?
Yes. Because every workload runs on one Apache Spark engine, IOMETE handles ML notebooks (Python, R, SQL) and streaming ingestion from Kafka, Kinesis, and Pulsar natively — without bolting on separate tools.
When is Starburst the better choice?
Starburst is a strong fit when your priority is federated SQL across many existing databases and warehouses without consolidating storage. If you want to own a complete lakehouse – storage, governance, and all workloads in your own infrastructure — IOMETE is the better fit.
Starting with IOMETE is simple. Book a demo with us today.
The IOMETE data platform helps you achieve more. Book a personalized demo and experience the impact firsthand.