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Icebreaker Technical Reference.


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FAQ

Icebreaker is recognizable in many ways, but we defintely do things differently.

Here are some of the most common questions we get.

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  • What exactly do you mean by *serverless* query platform?

    Traditionally, serverless means you offload server management to a public provider like Google BigQuery or Amazon Athena. You pay-as-you-go, but you lose control over where your data sits and how the underlying compute is managed.

    Icebreaker brings that same provider-grade infrastructure directly into your own VPC. We automate the backend IT—specifically using one-query-per-pod containerization to bin-pack your workloads, and take advantage of your negotiated compute and Spot pricing. You get the extraordinary efficiency of a public service, but it runs entirely on your private infrastructure.

  • Deploying a provider-grade serverless query platform in my VPC seems like a lot to manage. Is it overkill for my organization?

    It's actually the opposite of overkill—it's the ultimate lean setup. While "right-sizing" traditional warehouses or clusters requires constant tuning, Icebreaker's serverless model optimizes every query automatically.

  • Why would I deploy Icebreaker in my VPC?

    • Security: Your data never leaves your network.

    • Query-Level Economics: Because we execute queries in isolated pods that fill "gaps" in your existing idle capacity, it is significantly less expensive than sizing and maintaining dedicated clusters and warehouses.

    • Operational Simplicity: You stop worrying about routing queries or scaling instances; you simply run the query, and the platform handles the micro-scheduling automatically.

  • Does Icebreaker work with or replace Snowflake/Athena/Redshift/BigQuery?

    Icebreaker replaces SQL workloads that use Iceberg tables. Our perpective is there's no point in paying premium pricing for what are now commodity services.

  • Can I move my Spark jobs that run on Databricks and Amazon EMR to Icebreaker?

    Icebreaker will support Spark for distributed queries in the future. But you may still find value in Icebreaker now. Many jobs that run on distributed architectures can run just fine on large, single instances at the same "compute unit" cost.

  • Do I need to use Iceberg tables?

    Currently, yes. Icebreaker works with Iceberg tables.

  • What if I don't have Iceberg tables now? Can I still use Icebreaker?

    You can use Icebreaker in your ETL/ELT pipeline to write Iceberg tables and perform SQL transformations.

  • What else do I need besides Iceberg tables?

    Icebreaker currently runs in your AWS cloud account using AWS EC2 instances. You get to prioritize on-demand, reserved instance (RI), or spot pricing for your various workloads.

  • We negotiated a Private Pricing Agreement (PPA) or Enterprise Discount Program (EDP) with AWS for a huge discount on Reserved Instances (RI). Can I use it with Icebreaker?

    Icebreaker was inspired by organizations just like yours! Too often, organizations have loads of discounted compute capacity, which they use for non-data applications. They still pay for Snowflake, or Redshift, or BigQuery (the list goes on) for data processing! Instead, you can run your SQL jobs on Icebreaker, which uses available capacity on Reserved Instances (or spot instances for even more savings). See BYOC or DaaS to learn more.

  • Does Icebreaker work with my BI tool?

    Yes, Icebreaker provides endpoints that work with your BI tool.