This space is dedicated to conversations about scalable, Iceberg–based lakehouse architectures. Whether you’re exploring open lakehouse concepts, designing for analytics at scale, or sharing lessons learned from real-world implementations, you’re in the right place. Ask questions, share insights, and connect with others building modern, open data platforms—let’s learn and innovate together!
I’m excited to see this forum and to join the discussion. I have been exploring Qlik Open Lakehouse since the announcement and I am very impressed with it. I believe it will benefit all Qlik customers because it makes building and managing Iceberg-based lakehouses much simpler and more scalable.
I look forward to learning from others here and sharing experiences.
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I actually have the same question and would also like to better understand Qlik’s direction here.
From what I understand, it now seems possible to create transformations and data marts in an Open Lakehouse project when working with streaming file sources. However, for CDC and SaaS application sources, it looks like we currently only have landing and storage tasks available.
For me, that slightly reduces the cost-efficiency argument of the lakehouse approach, especially when many transformations still need to happen in a separate cloud data warehouse by mirroring the data.
Does Qlik have any roadmap plans to support transformations and data marts for CDC and SaaS sources directly within Open Lakehouse projects? Or is there a direction to support this through an external query engine, for example by connecting something like Amazon Athena to the project in the future?
Hello @stijnvaneven, that's also my impression, on Qlik Connect I saw some transformations been made with Streaming and File Sources but now using CDC or SaaS application sources.
So, the idea is use QTC for storage and landing and another tool to transform? Like Talend Studio, This is not clear on the architecture.
I hope that's not the intended direction, going to a separate transformation tool like Talend Studio for CDC/SaaS sources would mean losing a lot of what makes the Qlik Compose / Data Warehouse Automation experience valuable today (integrated modeling, data marts, lineage, orchestration all in one place).
Transform and DataMart task do not distinguish between streaming sources and CDC or SaaS sources. This means they can also be created in the Open Lakehouse Project. Please refer to the following YouTube video.
