Data Lakehouse 2.0

On Premise | Cloud | Hybrid

With IOMETE, you can enjoy the benefits of a data lakehouse with flexible deployment options, without breaking the bank. Whether you want to run it on-premises, in your private cloud, or on a public cloud like AWS, Azure, or GCP, your data will always remain securely within your control. IOMETE's modern architecture, which includes the Iceberg table format and powerful Spark engine, unifies your data in a single location, making it easy to run BI and ML/AI workloads on it.
A modern and open lakehouse

IOMETE is built on Apache Iceberg, a versatile table format that is gaining popularity for its ACID compliance, scalability, and open-source nature, making it a good choice for organizations that need to ensure the integrity of their data. IOMETE also includes a powerful Apache Spark engine that allows you to query petabytes of data in seconds.

Securely deployed where your data lives

You can deploy IOMETE on-premises, in the cloud or in a hybrid configuration. You can use object storage with MinIO or a compute cluster with Kubernetes. Our team fully manages the data lakehouse, including migration and maintenance.

With disruptive, transparent pricing

The prevalent compute-based pricing model favors greedy incumbent data vendors and the VC cartel that funds them. IOMETE's flat pricing is simple, predictable, and provides great value. Our customers save over 50% compared to Snowflake, Databricks, and Cloudera.

Sync. Prepare. Consume.

Unified data for analytics, ML and AI made easy.

Sync from a wide range of compatible data sources

or use query federation to unify your data for analytical and ML/AI workloads.
Sync or ingest from a wide range of compatible data sources

Use built-in serverless Spark jobs to sync data from your operational database and other data sources into a lakehouse or use a third party ELT tool to ingest your data.

Access your data with query federation

IOMETE allows you to query disparate datasources in the same system with the same SQL. Federated queries can access your object storage, relational databases, No-SQL system, all in the same query. IOMETE completely changes what is possible in this central data consumption layer. Easily join your lakehouse data with external JSON, CSV files without ingesting them to the lakehouse.

Enjoy the benefits of near real-time streaming

IOMETE's powerful Spark Job Cluster makes it easy to analyze realtime streaming data. With IOMETE, users can ingest and process large volumes of realtime data from a variety of sources - including IoT devices, social media feeds and financial transactions.


Transform, clean and organize your data with SQL, Spark and DBT.

Transform your data at any scale

Built-in Apache Spark can handle large datasets by dividing them into smaller partitions and processing them in parallel on in clusters. This makes it highly scalable, fast and suitable for up to petabytes datasets. Apache Spark is flexible and handles SQL, Java, Scala, and Python. IOMETE offers a seamless integration with DBT.

Run ad-hoc analysis with the SQL editor

The built-in SQL editor provides a toolkit to make it easy to write SQL queries with features such as search, autocomplete and schema explorer.

Organize your data with the built-in data catalog

The IOMETE data catalog provides Google-like search, index and discovery for your data. It also allows you to document the data you own so you can stay organized.

Manage data access and become compliant with data regulations

Leverage advanced data access controls to keep your data secure. IOMETE allows you to manage access on person or team level, as well as on table, row and column level and makes it easy to become and stay compliant with regulations such as SOC2, HIPAA and GDPR.


Run blazing-fast analytics, ML and AI models

and enjoy the benefits of having access to relevant, high-quality data for analysis and decision making by men and machines.
Run blazing-fast analytics on quality data

It’s very easy to connect IOMETE to your favorite BI tool - including Tableau, PowerBI, Metabase and Apache Superset - and enjoy the benefits of organized, high-quality data for analytical and dashboarding purposes.

ML and AI made easy

With features such as notebook service, training ML jobs on the Spark cluster and unlimited time-travel on the data lake, IOMETE makes it easy to run your ML and AI models whether it is on premise or in the cloud.

Explore IOMETE use cases

On premise and hybrid deployment options

Explore how IOMETE can be securely deployed in your trust perimeter.
IOMETE on premise deployment
Enjoy cloud-like performance with the benefits of on premise.
IOMETE hybrid deployment
Learn how to combine on premise and cloud with one platform to rule them all.
IOMETE private cloud deployment
Learn the benefits of running IOMETE in your private cloud.

Cloud-only deployment options

You want to know a little secret? We started out as a cloud-only data lakehouse. Even though we are now focused on on premise and hybrid deployments, IOMETE can also run on any major cloud.
Learn about the benefits of running IOMETE on AWS.
IOMETE on Azure
Learn about the benefits of running IOMETE on Azure.
IOMETE on Google Cloud
Learn about the benefits of running IOMETE on Google Cloud.

Featured Use Cases

Some interesting use cases.
Replace Cloudera with IOMETE
Better performance, better feature-set, lower price. A no brainer.
Add IOMETE as a data lake to the Snowflake warehouse
Benefit from IOMETE's usage independent pricing and cut your cloud bill in half.
Managed Iceberg solution
Leverage IOMETE as your fully-managed Apache Iceberg solution.
Want to learn more about our product or book a demo?


$0.10 per GB data stored per month and the first 100 GB is for-ever-free.
We built IOMETE because data infrastructure is too complex and too expensive. We have a desire to make it easy and cost effective. We realized early on that we must deliver on that from both a product and pricing perspective. That's why our pricing is straightforward and low. How low? You should be able to save at least 50% over any incumbent (e.g. Snowflake, Databricks, Cloudera). If not, we'll eat our shoe.