IOMETE hybrid deployment

Combine the benefits of on premise and cloud in one data lakehouse platform.
Use Case
Challenge

You may identify with one or more of the following situations

You may desire a modern, cloud-like data analytics platform but cannot fully rely on cloud deployments due to industry or federal regulations.
You have privacy and security concerns and want to fully own your data on-premise.
Scalability, robustness, and performance are top priorities.
You're tired of steep and fluctuating cloud bills and are considering repatriating fully to on-premise solutions but don't want to lose the benefits cloud has to offer.
Solution

IOMETE hybrid deployment allows you to reap the benefits of on premise and cloud in one data lakehouse platform.

Deploy a modern and cloud-native data analytics platform within your on-premise environment. Have the flexibility of combining multi-cloud, multi-region and on premise deployments, in a unified environment.
The IOMETE lakehouse combines the strengths of data lakes and data warehouses, providing the scalability and flexibility of a data lake with the structure of a data warehouse.
IOMETE charges a flat fee per GB stored rather than the prevalent usage-based compute cost models. Save big, budget your costs upfront, and don't worry about fluctuating bills.
IOMETE is a fully managed service. This means no updates or maintenance for you to worry about. You can focus on your data and business.

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Free Plan
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Resources

Guides

How to install IOMETE
Easily install IOMETE on AWS using Terraform and enjoy the benefits of a cloud lakehouse platform.
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Querying Files in AWS S3
Effortlessly run analytics over the managed Lakehouse and any external files (JSON, CSV, ORC, Parquet) stored in the AWS S3 bucket.
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Getting Started with Spark Jobs
This guide aims to help you get familiar with getting started with writing your first Spark Job and deploying in the IOMETE platform.
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Docs

Virtual lakehouses
A virtual lakehouse is a cluster of compute resources that provide the required resources, such as CPU, and memory, to perform the querying processing.
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Iceberg tables and Spark
IOMETE features Apache Iceberg as its table format and uses Apache Spark as its compute engine.
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The SQL editor
This guide aims to help you get familiar with getting startedThe SQL Editor is where you run queries on your dataset and get results.with writing your first Spark Job and deploying in the IOMETE platform.
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Learn more in a 30 min demo discovery call.