One line from Snowflake Summit 2026 stood out above everything else.
Christian Kleinerman, EVP of Product at Snowflake:
"We do not want any of you spending money with Snowflake, in any use case, if you are not getting more value in return."
It's a refreshing commitment, and it points directly at the cost efficiency conversation we've been having with customers around open lakehouse architectures.
Here's the core argument: data movement doesn't directly generate value. It's the necessary plumbing that makes data accessible for the things that *do* generate value: analytics, AI, and decisions. Every dollar spent copying and moving data is a dollar that never gets applied to those outcomes.
The Qlik Open Lakehouse addresses that problem directly. Write once, cost effectively with the necessary interoperability to read that data from everywhere.
We performed a benchmark to demonstrate the potential savings that a CDC ingestion with Qlik Open Lakehouse can achieve when compared with a direct ingestion into a data warehouse, and the results demonstrated an 89% reduction in cost, with a 2.5x improvement in data freshness:
With this as a baseline, and the fact that the industry agrees that the average customer spends 30-50% of their data warehouse budget on ingestion alone, there’s a tremendous opportunity for a significant adjustment in where you spend your money, and specifically allocating your dollars to high value outcomes.
These cost savings do you no good if your data cannot be accessed from everywhere you need to. Many organizations need to be able to consume data from a variety of engines, potentially one or more data warehouses such as Snowflake or Databricks, and/or query engines such as Spark, Trino, AWS Athena, DuckDB, etc...
To simplify interoperability of Qlik Open Lakehouse tables, Zero Copy Mirrors can be created in your data warehouses that allow for your Iceberg tables to be directly queried, without having to copy and move the data around. Mirrors, combined with direct access from your query engine of choice, means you get the true freedom to query your data using the best consumption engine that supports your use case, not the one forced upon you by your data platform.
Drive cost out of plumbing. Reinvest in the value. That's the Qlik Open Lakehouse approach, and the industry just spent a week in San Francisco agreeing with it.