Data Lakehouse 2.0

On Premise | Cloud | Hybrid

Analyze multi-terabyte to petabyte-scale data seamlessly across on-premise and/or cloud environments while maintaining full ownership of your data.

A modern and open lakehouse

IOMETE is built on open Apache Iceberg. Get access to ACID transactions, time travel, snapshots, schema evolution, data versioning, concurrency control, metadata management, and partitioning. Powered by the Apache Spark engine, IOMETE is fast, versatile, and scalable.

Securely deployed where your data lives

IOMETE can be deployed on-premises in your data centers, in the cloud or in a hybrid configuration. In all cases the data does not leave your trust perimeter, guaranteeing maximum data security and ownership.

With disruptive, transparent pricing

We know: cost matter. Compute as much as you want for a flat predictable price. Save 50% or more over incumbents and get access to a fully-managed modern data lakehouse platform.

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Sync. Prepare. Consume.

Unified data for analytics, ML and AI made easy.

SYNC

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.

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.

PREPARE

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 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. This makes it easy to become and stay compliant with regulations such as SOC2, HIPAA and GDPR.

CONSUME

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.