Data Lakehouse 2.0
On Premise | Cloud | Hybrid
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.
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.
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.
Sync 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.
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.
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.
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.
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.
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.
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
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.
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.
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On premise and hybrid deployment options
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