IOMETE and Amazon Athena

You are using AWS Athena and are looking to transition to a modern and open lakehouse solution.
Use Case

You may identify with one or more of the following situations

You are searching for a comprehensive, end-to-end lakehouse platform that provides a seamless experience for all data-related tasks, from data ingestion to data analysis and reporting, eliminating the need for multiple tools and reducing complexity
You realize that Athena's pay-per-data-scan cost model doesn't really work at larger scales and with bigger team sizes. Poorly optimized queries can lead to full table scans and unexpected bills
You realize that Athena has limitations in handling high-concurrency workloads and unpredictable performance issues at times, which can lead to query throttling or delays. You are looking for better performance and scalability
You are cost-conscious. Data size typically grows fast, and you want a cost-efficient solution

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

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 is based on Apache Spark and Iceberg, which provide better performance and scalability than Athena. With IOMETE, you can handle high-concurrency workloads with ease without experiencing query throttling or delays
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 provides a cost-efficient and predictable flat-fee pricing model independent of the amount of data scanned. With IOMETE, you can store and query as much data as you need without worrying about unexpected bills. This pricing model makes IOMETE a better choice for larger scales and bigger teams, where cost can be a significant factor

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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.