IOMETE and Financial Institutions

Revolutionize Finance Analytics: IOMETE's Cloud-Prem Lakehouse for Financial Institutions.
Use Case

You are experiencing one or more of the following challenges

Data security and compliance are critical, and you want to own your data 100%, either fully in your cloud or on-premises environment
Scalability, robustness, and performance are the top priorities
You are looking for a modern and open lakehouse solution that is flexible and open, rather than a proprietary solution, to avoid vendor lock-in
You are cost-conscious and want a cost-efficient solution, especially since data size tends to grow rapidly

IOMETE is a modern cloud-prem lakehouse that provides a scalable, cost-effective, and secure data lakehouse and data warehouse solution in your own cloud environment

IOMETE delivers a highly secure data lakehouse solution, fully deployable in your cloud or on-premises environment. With IOMETE, you maintain complete control over your data and easily achieve compliances with SOC2, GDPR, and other data privacy and security regulations
With IOMETE, users with less technical expertise can perform data science and analytics at scale with the help of a unified analytics platform that provides an easy way to build end-to-end data pipelines and ML use cases
IOMETE offers a modern, open lakehouse solution built on Apache Spark and Iceberg, designed for flexibility and openness. This approach prevents vendor lock-in and grants you the freedom to choose the tools and services that suit your financial institution best
IOMETE charges a low, flat monthly fee instead of a heavily marked-up pay-per-hour consumption model, which can quickly become expensive as data sizes increase. Save big, budget your costs upfront, and don't worry about fluctuating bills

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Free Plan
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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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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.