IOMETE and Snowflake

Augment Snowflake with IOMETE to reduce cost and improve performance.
Use Case

You may identify with one or more of the following situations

You want to avoid vendor lock-in. Having all your data on proprietary Snowflake may limit your flexibility and potentially increase costs in the long run.
You are using Snowflake and it is becoming increasingly costly. As data tends to grow over time, Snowflake’s consumption-based billing gets continuously more expensive for you, while the functionality they deliver does not necessarily change.
You want to keep sensitive data in your own cloud account to be compliant with regulations and/or privacy data ownership considerations and only send non-sensitive data to Snowflake.
You are looking for a modern and open lakehouse solution that is flexible and open rather than a proprietary solution.

IOMETE is a modern cloud-prem lakehouse that provides a scalable, cost-effective, and secure data lake and data warehouse solution

IOMETE is a fully-managed service and completely runs in the customer's cloud environment.
IOMETE has a transparent flat-fee cost model. You can optimize costs by using AWS’s reserved instances, discounts, spot instances, and other cloud optimizations in AWS to reduce your costs by 50% or more. IOMETE will handle the heavy processing while using Snowflake as their data warehouse for the last mile analytics.
Improve your data platform capabilities by using the Apache Spark & Iceberg-based IOMETE platform. This platform covers data science use cases, with Apache Spark jobs and a notebook service available. Moreover, the built-in query federation allows you to query operational data sources directly without building any ingestion data pipeline.
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.

Combine Snowflake’s and IOMETE strengths to cut costs by > 50% while improving performance

You might be using Snowflake for all compute jobs (top scenario in visual below). This can get expensive quickly due to Snowflake's consumption-based revenue model: the more you use, the more you pay. IOMETE's lakehouse architecture makes it perfectly suited for the heavy lifting in the bronze and silver tiers (middle scenario). We aim for 50% or more savings on your cloud spend. We do this by transferring compute volume from Snowflake to IOMETE. How? We only charge a flat monthly platform fee and will adjust the platform fee to the point where you realize 50% savings. In the bottom scenario, IOMETE replaces Snowflake and we see cost savings of > 50%.

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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.