How to choose the right compute engine for the workload
Live demo
November 17, 2026
11 a.m EST
Virtual
Jamie Cole
Eric O'Connor
Jack Lowery
How Open Data Infrastructure delivers flexibility, lowers cost and makes AI more achievable.
How to choose engines by workload, budget and team without giving up governance.
Live demo, Lake Compute: run models on Lake Compute and Snowflake in the same project to reduce warehouse costs.
Live demo, local and AI development: how your laptop talks directly to your data lake with Fivetran and DuckDB, on compute you already own.
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When data lives in one warehouse, every workload runs on that warehouse. When it lives in an open data lake, compute becomes a decision you make per workload, not a long-term commitment to a vendor. In some cases, you can even use different engines within the same job as we’ll demonstrate.
This session matches the engine to the job: batch processing, analytics, local development or AI agent access. You can try new tools, adopt new capabilities and pick the most cost-effective option for each workload. That saves engineers time and the business money.
This is session 2 of 3 in the Open Data Infrastructure series. Each session stands alone.
- Session 1 on Nov 10: The modern data lake: the governed foundation for your AI. Save your seat.
- Session 3 on Nov 24: Build a Context Layer to Connect AI to Your Data. Save your seat.
How Open Data Infrastructure delivers flexibility, lowers cost and makes AI more achievable.
How to choose engines by workload, budget and team without giving up governance.
Live demo, Lake Compute: run models on Lake Compute and Snowflake in the same project to reduce warehouse costs.
Live demo, local and AI development: how your laptop talks directly to your data lake with Fivetran and DuckDB, on compute you already own.
Jamie Cole
Eric O'Connor
Jack Lowery
Jamie Cole
Eric O'Connor
Jack Lowery
When data lives in one warehouse, every workload runs on that warehouse. When it lives in an open data lake, compute becomes a decision you make per workload, not a long-term commitment to a vendor. In some cases, you can even use different engines within the same job as we’ll demonstrate.
This session matches the engine to the job: batch processing, analytics, local development or AI agent access. You can try new tools, adopt new capabilities and pick the most cost-effective option for each workload. That saves engineers time and the business money.
This is session 2 of 3 in the Open Data Infrastructure series. Each session stands alone.
- Session 1 on Nov 10: The modern data lake: the governed foundation for your AI. Save your seat.
- Session 3 on Nov 24: Build a Context Layer to Connect AI to Your Data. Save your seat.